Category Archives: Interviews

Zimbio – Interview with Tony Mamone

August 22, 2006 7:32 pm ⋅ Leave a Comment ⋅

I’m pleased to welcome Tony Mamone, CEO and co-founder of Zimbio, to the Search Lounge. Zimbio is a free community site that allows anyone to create a portal on any topic. There are portals on all kinds of topics ranging from Film Noir to Soccer in Uruguay to Stephen Colbert to…on and on…
Zimbio recently went from invite-only to being open to the public, so go check it out and create a portal on your favorite topic.

Hi Tony. Thanks for taking the time to answer a few questions. Can you give us an introduction to how people get started with using Zimbio?

Zimbio is a community site that helps people research and learn about any topic. You can browse the site to learn about topics ranging from the Tour de France to Election 2006 to Nutrition Education. Each topic has its own portal, which includes a collaborative directory of recommended websites, photos, and other media about the specific topic, and related commentary by other members in the form of a group blog.

You can also start a new topic to help you organize your research and connect with other people who share your interests, or to help you promote your experience and knowledge in a particular subject

What are some of your favorite portals people have created on Zimbio? And also what are some of the most popular portals?

Right now, Tamara Hoover seems to be popular. She’s the Texas art teacher who’s been battling the local school board about some photos that were posted on flickr. We’re also starting to see more and more interest in political portals such as Hezbollah, “Election 2006″, and Senator Kay Hutchison.

In terms of my current favorites, here are a couple of interesting portals:

. McMurdo Station Antarctica – it was one of our first portals, and has some great blogs and photos about scientists doing research in Antartica. Plus, I like penguins.

. Bird Flu – This portal has great links about Avian Flu and the spread of H5N1.

. Web 2.0 Company Blogs – This one includes an organized list of blog feeds about web start-ups.

. Energy Conservation – People have shared tips about ways to conserve energy. I also like to scan for recent news and blogs about the topic.

. Africa Travel – I’d love to go on a safari, but for now I just check out the photos and blogs that people post.

Are there portals you’ve seen that you never would have imagined would be created? I’ve seen some unusual ones myself, like the one about Meat Thievery.

Who knew there were groups of folks interested in Bookcrossing or Rejected Cartoons. Its really neat to see what people build. And yes, gotta love the list of recent meat thieves!

Every time a user-generated site is created people wonder what motivates the users. I’m thinking of ODP, Wikipedia, flickr, etc. So, *ahem*, what motivates people to use Zimbio?

We make it quicker and easier for you to learn about a new topic by helping you benefit from the wisdom and work of others. You can piggyback on research that’s already been done by finding existing portals. You can then post questions or just browse the recommended links and articles on the site. Or if we don’t already cover the topic you’re interested in, you can start a new portal and use our bookmarking tools to organize your online research and connect with like-minded people. It’s really easy to start a new topic and once you do, you get a browser button that helps save and organize links, feeds, and photos.

If you are a blogger or someone who is passionate about a particular subject, you can use Zimbio to get your message out to a wider audience. You can dual post blog articles on Zimbio and link back to your personal blog. Or you can start a portal about your favorite organization, social mission, political candidate, etc in order to raise awareness of the issue.

Which kinds of topics work best as portals?

The more specific the topic, the better. For instance, Gilad Shalit or Senator Hillary Clinton instead of “Politics.” Zimbio returns great results for related news and blogs when the topic is distinct. Other members also tend to share their opinions in the group blog or forum when the topic is well defined.

How are search engines handling Zimbio pages? Are the crawlers keeping up with the rapidly changing content you guys have? Assuming search engine traffic is an important part of your business, what steps are you guys taking to generate search engine referrals?

We index well in Google. Googlebot found us right away and we now show up in search results for searches such as Cyril Dessel, Runescape Hacks, and Carlos Mencia Comedy. We’re still a very new site, so hopefully we’ll start to see more traction from Yahoo and MSN soon. We concentrate our efforts on making it easy for people to post content; then make that content available to the search engines.

Zimbio portals have a ton of information. As a user yourself, what’s the first part of the page you look at when you go to a new portal?

First, I get myself informed about the topic. I read the description in “About this portal” and check out the top couple of recommended inks. Once I’m up to speed, I try to stay informed by scanning recent news and blogs in the trackers. I also like to check out other people’s opinion about the topic – and for that I usually read the group blog or forum.

How are you getting the word out about Zimbio now that you’ve gone beyond the invite-only stage?

Zimbio is a community site – it has a grassroots feel to it. We encourage our existing members to tell friends and colleagues about the site. We also respond to bloggers who want to write about or review Zimbio.

What kind of new features can we expect to see in the future?

Soon we’ll begin to feature specific categories on Zimbio. Our first featured category will be Politics, starting in September. We’ll be featuring bloggers who write about politicians, candidates, elections, and political issues. Political bloggers can sign up for a profile on Zimbio and dual post their blog entries to appropriate portals. We’ll then feature the best blog posts and link back to the original blogs. It’s a great way for bloggers to get the word out about their personal sites.

Thanks for your time! Anything else you’d like to add?

We always appreciate feedback and ideas. So if anyone would like to make suggestions or learn more about Zimbio – please visit our company blog at http://www.zimbio.com/portal/zimbio.

Posted in: General, Interviews

A9 – Interview with Barnaby Dorfman VP of Local Search

June 4, 2005 4:23 pm ⋅

I am very pleased to feature an interview with Barnaby Dorfman from A9. (This interview was conducted at the end of March, but due to some issues on my end I was unable to publish it until now.)

Hi Barnaby, thank you for taking the time to answer some questions about A9’s visual yellow pages. Can you give some background about what your role is at A9?

My pleasure. As the VP of Local Search, I lead a team that created and continues to develop the Yellow Pages on A9.com and Amazon.com. Here’s a short bio about me:

Barnaby Dorfman is vice president of local search at A9.com, Amazon.com’s search subsidiary. He leads the team that developed the A9.com Yellow Pages. Prior to joining A9.com, Barnaby was director of services at the Internet Movie Database (IMDb.com), also a subsidiary of Amazon.com, where he created IMDbPro.com.

Barnaby joined Amazon.com in 1999 when the company acquired Bibliofind.com, where he was general manager. His first role was leading a team to develop product categories in the Amazon.com marketplace.

Barnaby’s past positions include technology consulting to Fortune 500 companies.

He earned a bachelor of science in international business from California State University of San Francisco and a master of business administration from the Amos Tuck School of Business at Dartmouth College

Since A9’s visual yellow pages is different from the local search available at other major engines like Google and Yahoo, what kinds of user missions are best served by it? When is visual search particularly useful? How about any unexpected results that make you scratch your head and might be areas for improvement?
On A9, our goal is to make search more efficient. At Amazon.com, our goal is to be the best place online for users to find and discover things that they want to buy. If a picture is worth a thousand words, then our >20 million images have created a lot of value for users and online shoppers relative to a simple directory with just a name address, telephone number and a few categories.

Businesses put a lot of effort into selecting a location, creating a storefront, and branding themselves through signage and displays. The Block View ™ feature allows all of that work to be conveyed, via the web, to potential customers.

Online shoppers can now get a sense of place before visiting. We have all had the experience of being surprised (positively and negatively) when visiting a business for the first time, often found via print yellow pages. Using the A9.com Yellow Pages, you can get a feel for the neighborhood, other businesses in the area, even see the parking situation. Online shoppers can now save time when planning a day of shopping in physical stores.

We have definitely been surprised at how users have created collections of links to interesting images from Block View ™, which have shown up in a number of blogs. Turns out that you get some pretty artistic pictures without trying when you capture millions of images. We’d like explore additional ways for people to find and share interesting things they see in Block View ™.

Would you mind sharing a personal anecdote about something you recently used visual yellow pages to successfully search for?
Sure, last Friday I wanted to get together with some friend in San Francisco. I really like Ethiopian food and I found this restaurant in our Yellow Pages: http://www.amazon.com/gp/yp/B0004AN77O/. Liking the look of the place and area, I used our “Click to Call” feature to make a reservation for free. The restaurant is about 90 minutes from our offices, so before going I printed a map and directions from the site. Beyond that, I “walked” up and down the street and found that there was a parking garage 1 block away. When we got near, I knew exactly where we were and where to park, even though I’d never been there. I’d sent the above link to my friends and they found it no problem as well. We all arrived within minutes of each other and a good time was had by all!
Furthermore, I moved to the San Francisco Bay Area last year and the A9.com Yellow Pages have made the settling in process much easier than past moves.

I find the exterior photos of businesses to be useful. But for a lot of businesses, like restaurants, I would love to also see interior shots. Hopefully businesses and users will add these themselves, but is there any plan to encourage this process?
Absolutely, we have given the links prominent placement on the page and will be reaching out in a variety of ways to encourage submissions. If you think about it, there is significant overlap between the busy people who run local businesses and the 47 million shoppers who took advantage of the convenience and selection at Amazon.com in the last year. Additionally, beyond interiors we’d like to see other kinds of images uploaded, including logos, maps, menus, and marketing collateral.

On the -Here’s how we did it- page, it says “The whole process (except for the driving!) is completely automatic”. How successful was the process of using GPS data to associate businesses with photos? And what kind of metadata ends up being associated with a business? As a follow-up, since the process is automated, is that why sometimes the default image is just slightly off?
We feel it has been very successful and extremely efficient. With nearly 1 million businesses covered in less than a year, this simply would not have been possible without recent technology innovations. As you surmised, the automated nature of our collection process allows us to reliably display a segment of the block near where the business is located, ergo the name “Block View ™.” Given the irregular nature of the physical world, deciding what view best represents the business is subjective, which is where our user community comes in. Below each thumbnail image, there is a check box titled “Best Image?” that users can click to vote on what they think is the most representative picture. This builds on other community created content at Amazon.com, including customer reviews.

I would love to be able to start with a location on a map and then work backwards to see photos of nearby businesses. Is that something that’s in the works?
We listen carefully to what our customers tell us they want, and you are not the first to suggest this. We are still in Beta and looking at many of enhancements. You can expect to see the site evolving.

What happens with businesses that were missed in the first round? And what about Canada and other countries?
This is an ongoing program for us. We will continue to expand coverage in the markets already included in Block View(tm) and add new geographies. Right now our focus is on the United States.

Do you have the luxury of conducting user tests to gauge success rates? And do you analyze query logs to see what users are searching for?
We do. In fact, we are very focused on customer interaction with our site as well as direct feedback. We believe that this customer focus is the key to continuous improvement.

Can businesses grab A9’s photos and use them on their own sites?
Our current site license and user agreement do not explicitly allow for this. However, I would like to develop ways to allow businesses to share in the use of these images.

Can a person or business request the removal of images due to unfavorable content, poor photo quality, privacy issues, or any other reason?
A9.com and Amazon.com take privacy very seriously. There is an “opt out information” link on every detail page. This takes users to a form they can fill in to report any individual concern they may have.

Are you considering ways to integrate web search with yellow pages? Right now I don’t see home pages or other URLs associated with business listings. Plus things like external reviews, articles, etc.
Over time will we continuously expand the amount of information available for each business. Right now, anyone, including business owners and managers, can submit information directly via the website. There is a button on each business detail page titled “Update Business Info.” This links to a form with fields for a URL/Link to the business website, description of products/services, hours of operation, etc….basically anything a business might want to communicate to prospective customers. After submission, we review and publish the content for free. Here’s an example of a business that added a link to their website: http://www.amazon.com/gp/yp/B0005P1Q8K

Visual yellow pages is a distinctive way to think about local search. Where did this idea come from to integrate photographs with business listings?
We have a long tradition of using images to help online shoppers find and discover things they want to buy…this is a natural extension. Consider books, which started with little more than title, author, and price. Now you can search and view millions of pages of over 120,000 books through Search Inside the Book(tm). Similarly, you can see millions of images of businesses from your office or home computer using Block View(tm).

Visual yellow pages is a fun thing to play around with. But how do you answer people who say that it’s more of a novelty than a useful search tool? (In case you’re wondering, my personal position is somewhere in the middle. I think as it stands now it is useful, but I see the current implementation as being just the first step of something bigger.)
First, I’d say try it out, especially to find and visit a business you’ve never been to. The feeling of deja vu you’ll get when you arrive is quite impressive. Second, there is a lot more to our A9.com Yellow Pages than block view. We have extended the Amazon.com user interface to include listings for more than 14 million businesses. This approach to finding and discovering products/services is familiar to and used regularly by tens of millions of online shoppers. Furthermore, we are offering Click to Call, an easy to use calling service to all businesses and users for free. Overall, our goal is to make it easier than ever for customers and businesses to find each other.

Thank you very much for your time. Is there anything else you would like to add?
Thank you! I’d just close by encouraging businesses to use our free services to promote their businesses and shoppers to explore their cities and towns in this new way.

Posted in: General, Interviews, Local Search

Clusty -A Brief Interview About Clustering

February 25, 2005 7:31 am ⋅

Clusty is a web search tool that clusters results. It is a meta-search engine so all results are pulled from other engines. Clustered results help make it easier to quickly get a good understanding of the broad range of information available for certain topics. Clustering also allows users the option to browse by clicking on narrower, broader, or related topics. Vivisimo, the company that makes Clusty, has been clustering results for a while, but recently they decided to switch their web search traffic to Clusty. Vivisimo.com still offers web search, but is really more of a corporate page that describes their enterprise search solutions.

Back in October I wrote a review of Clusty for the Search Lounge.

This email interview was conducted with Director of Marketing Saman Haqqi.

***************************

Although clustering algorithms have been in the information profession for a while, and even Vivisimo and a couple of other companies have been around for several years, why do you think clustering web results hasn’t really gained much attention with the general public until recently?
The benefits of a clustering engine over simple ranking engines are increasingly recognized by the world at large and are validated by the growing traffic at clusty.com and the adoption of the technology by AOL for its new public search site at www.aol.com. Now one in every eight web searches offers clustered results.

Documents can appear in multiple clusters. How does the clustering engine determine the maximum number of clusters a document should appear in? And, just out of curiosity, do you know the average number of clusters per document? (I’d guess between 2 and 3…)
On average, a document can appear in about 1.7 clusters which seems to be very close to Yahoo’s humanly indexed directory where a document can fall in about 1.6 categories.

I notice that Wikipedia results often show up high in the results. Is there any particular reason for this? Are certain sources weighted higher than others?
Since web searchers typically do not use tabs to focus search results, Clusty dynamically gives higher weight to some sources like wikipedia, shopping, weather sites, image databases etc. depending upon the nature of the query. Look for several new key matches to be introduced over the next few months.

I’m curious about cluster depth. The deepest I have seen clusters go is three levels, though generally they seem to max out at two levels deep. Is this something that is pre-set? Or might the depth increase over time as you continue to develop your clustering technology?
The depth of clusters is determined by the number of results in a cluster and the variety amongst them.

How does your company evaluate the relevancy of clusters being returned for searches? Is there a formal process in place for doing this?
We are the most exacting critics of our solution and are always working to improve the quality and relevancy of our clusters.

Vivisimo has a brief, but helpful, white paper called How the Vivisimo Clustering Engine Works. The white paper states that the clustering engine “Does not use a predefined taxonomy or controlled vocabulary…”. Why is that? Wouldn’t it make sense in some cases to overlay the clustering engine’s results on top of subject taxonomies or ontologies? A blended version would allow for scale, while at the same time taking advantage of human categorization.
Clustering overlays well with existing taxonomies and pre-defined categories.

Although not specific to a question I asked, here is some general information about the power of clustering that was included in the response I received.
At Vivisimo we believe that Web searching needs to evolve beyond ‘ranking engines’ that simply list undifferentiated page results ranked by popularity, freshness and links – criteria that don’t do enough to make search results useful to searchers. Clustering lets users view results organized into categories like books organized neatly in bookshelves instead of being randomly piled on the floor. It allows users to quickly overview at least ten times as many results as they would with ranking engines where users rarely go beyond the first page.
Similar results are grouped together so users can not only focus on the result that matches their interest but can also see other similar results easily. A simple ranking engine would have such similar results spread over several pages. Finally, the clustering allows deeper results which would otherwise be buried in later pages to rise to the top.

Key features:
Clusty.com is an implementation of our search engine, clustering engine and content integrator.

The clustering engine processes the text in search result summaries to group the results into folders. This ensures that clusters are returned within milliseconds.

Clusters are ranked based upon an advanced algorithm that accounts for the ranking of results by the underlying search engines, number of results, frequency etc.

Posted in: Clustering Engines, General, Interviews

BrainBoost – Interview with Founder Assaf Rozenblatt

February 7, 2005 3:56 pm ⋅

BrainBoost is a natural language search engine. Ask BrainBoost questions in plain English and you’ll get answers in plain English. BrainBoost is automated and uses no human editorial invention. The legend goes that BrainBoost was created by 24-year-old software programmer Assaf Rozenblatt. It took him a year to build it and he built it so that his fiancé could better do her college research.

For more information and analysis, check out the review of BrainBoost I did for the Search Lounge.

***
Hi Assaf, thank you so much for joining me here at the Search Lounge. I know you started BrainBoost, but what exactly is your role these days? And can you provide some more background about the size and structure of the company?

We are a very small team at the moment, with only a handful of developers.
We are still primarily focused on development, but we will be switching gears soon to the sales and marketing of our licensable AnswerRank technology.
I am still very hands-on with the software development and continually help improve the technology on an ongoing basis.

A big issue in Internet search is evaluating the trustworthiness of sources. This issue is amplified in BrainBoost because the answers are shown right on the search results page and do not require users to click through to investigate the trustworthiness of the source. For example, for the search what is the population of Scotland?, the first three answers are slightly different (5.2 million, 5.1 million, just over 5 million. Like I said, just a slight difference.) Maybe if you included a published/crawled date, would that help? Or some kind of page rank metric? Do you have any suggestions for how BrainBoost users should address this issue?

We are currently working on a PageRank like system to help identify trustworthy sources.

How do you evaluate the relevancy and quality of the results that are returned on BrainBoost? Do you have a formal process in place for doing this? And, what subjects or types of queries do you think BrainBoost is particularly good at? How about subjects or types of queries that need some improvement?

For QA, we compiled a database of common questions and manually researched the answers for each of them. We then run the questions through the BrainBoost engine, which in turn automatically goes out to find answers. Precision is then easily determined by comparing what percent of the automatically generated BrainBoost answers match our manually found answers

There really isn’t a question type that is problematic for us at this time.

BrainBoost is 100% automated, but would you consider blending BrainBoost’s technology with some editorial content or mapping of results for certain types of queries?

Extracting answers from unstructured documents is what really sets us apart from existing ‘Answer Engines’ like Ask Jeeves and the new MSN search. It’s a much trickier problem to solve, and we are going to continue focusing on it for the time being.

Can you provide any insight into how BrainBoost reformulates a query when it sends it to another engine? Any chance you might be willing to provide an example of how this works?

Query reformulation helps ensure search engines return web pages that most likely contain answers somewhere within them. A simple example: “what does NASA stand for” gets reformulated into “NASA stands for”. This simple reordering of words (and the conjugation of the verb) greatly boosts the likelihood that relevant documents are returned by the engines. With larger and especially multipart questions this can get very complicated.

There’s something I don’t quite understand about BrainBoost. I enter a search on BB; BB reformulates my query and sends the new query against other engines; the other engines provide results; BB gathers those results and ranks them. OK, so here’s the question: how does BB take a result from another engine and then show a different description (and title?) than what I would see on the other engine? Or am I missing a piece of the puzzle?

BrainBoost does not just display the results it gathers from other engines. It merely uses those results as it’s starting point. The core technology of BrainBoost is a system we call AnswerRank. The AnswerRank system is given a question and a collection of documents. AnswerRank then analyzes the documents line by line and automatically extracts the very best answers from those documents. The top few hundred search results from the popular engines are what we feed into AnswerRank. BrainBoost begins where the search engines leave off.

Does BrainBoost give a higher weight to certain sources? How about results from certain engines?

No, not at this time. All sources begin processing with an equal weight.

I’ve noticed that it matters if I don’t format my search like a question. Compare these two queries: population of Scotland vs. what is the population of Scotland?. Is that done on purpose?

BrainBoost pays close attention to all words in the question. The type of words you use and the order in which you use them determines what classification, or algorithm, BrainBoost will use to answer your question. Whereas most search engines ignore words like ‘what’, ‘where’, ‘when’ and ‘how’, BrainBoost very much relies on them. In this case, the wording of the two questions resulted in two distinct classifications.

Sometimes I see repeat phrases being displayed, such as for the query What is BrainBoost, the following phrase is repeated several times:
-BrainBoost is a Question Answering search engine.-
This probably is not too big a deal, and in fact it may even be a good thing because it shows agreement, but what is your opinion about it?

We chose not to filter out answers that provide the same information in slightly different ways. Like you said, it really does help with identifying agreement towards a specific answer.

I read some helpful information you posted about BrainBoost in a thread on Search Guild. You wrote: “BrainBoost classifies incoming questions into distinct categories. Classification enables BrainBoost to predict what lexical properties the answer will most likely contain.” Can you expound on this? Do you classify searches based on the subject or topic of the search? Or do you parse the query to look for clues in the phrasing of the search? Or…?

Its best to give an example: When asked “how long do cats live?” BrainBoost recognizes that the user is looking for sentences that quantify the answer in terms of years/months/weeks etc. Responding with an answer that talks about inches/feet/centimeters would not be very intelligent at all. BrainBoost has many dozens of these types of classifications, all of which help ensure suitable answers are returned.

It seems like I hear very little about BrainBoost. Are you purposefully trying to keep a low profile? Or might that change in the future? I like BrainBoost and since it is so easy to use I think a lot of other people would like it too.

Yes, we have been trying to keep a low profile. It’s given us the luxury of time we needed to perfect our AnswerRank system.

A considerable amount of time was also spent on packaging AnswerRank technology into a licensable software component that can be ‘plugged into’ any existing keyword-based search system, allowing for companies to add Question Answering to their existing in-house search.

What do you see as the current state of natural search engines on the web? Would you care to predict for us what the world of natural search will look like a couple years from now?

I think Natural Language question answering mixed with sophisticated personalization is the future of search.

Lastly, what is your favorite drink?

Triple Grande Latte

Assaf, thank you for your time. Is there anything else you would like to add?

Thanks for your time Chris.

Posted in: General, Interviews, Natural Language Engines

Findory – Interview with CEO Greg Linden

January 7, 2005 11:49 pm ⋅

The Search Lounge is very pleased to feature an exclusive interview with Greg Linden, founder and CEO of Findory. Findory is a unique service. It’s not quite a search engine, it’s not quite an RSS subscription tool, and it’s not quite a news aggregator site. So what is it then? I’ll quote Greg from an email he sent me: “…Findory isn’t a normal search engine. The primary focus of Findory isn’t search. The primary focus is discovery. The site learns your interests from the articles you read, searches thousands of sources for you, and surfaces interesting news articles and new sources. It’s like a newspaper built just for you. Quite a bit different than your average search engine.”

Findory shows you blog entries and news stories that match your reading patterns. And you do not have to enter a single bit of information about yourself. You do not even need to register to use the basic features. All you have to do is visit Findory’s homepage and either search or browse the listings. Then every time you click on a link to read it, Findory (I think) analyzes the page’s content and also checks to see who else clicked on that link and what else they have clicked on. Then when you return to the Findory.com homepage there will be links that Findory thinks you will be interested in. Although the back-end technology may not be crystal clear, it is actually very simple and powerful to use.

Greg also maintains a very good blog that I read constantly called Geeking with Greg. He writes about search, RSS, and other Internet topics. For several years Greg worked on personalization features for Amazon.com.

This interview was conducted exclusively via email.

Hi Greg, thanks for joining us at the Search Lounge. It is a pleasure to have you with us. Would you mind starting off by giving a bit of background information about how Findory fits into a user’s repertoire of online information tools? In other words, what are the benefit for those readers who have yet to try Findory?

Imagine the front page of a newspaper unique to you, emphasizing the news of the day you need to see. Findory is a personalized newspaper that learns your interests and builds a front page of news stories specifically for you.

Findory helps you read the news faster and more efficiently. Rather than skimming many sites to try to find the news of the day, Findory brings all the daily news to one spot, sorting news from thousands of worldwide sources. You will find articles you might otherwise miss while getting broad coverage of major news events.

Unlike news aggregators such as Google News, Findory is personalized to you, focusing your attention on the news you need. Unlike customized news sites such as My Yahoo, Findory requires no effort to use. You do not have to specify categories or keywords; Findory learns what news you want to see just from the articles you read.

Any plans to offer users a personalized interface to go with personalized listings? As a user, I would be particularly interested in changing the category ontology on the top page to promote subjects I am interested in.

It’s a great suggestion. We have built Findory to be super easy to use. No effort. No registration. Just read news and the front page gets better and better.

But some of our readers are interested in customizing the Findory front page. We will be launching more customization features over time, but our site will always remain focused on being easy to use, no effort required.

Would you mind shedding some light on whether Findory crawls and indexes its own search results, or whether they are pulled from other engines? And as a follow-up, is the search algorithm built in-house?

Findory has its own crawl of thousands of news sources and weblogs.

Our personalization technology was designed and developed by Findory. The personalization engine and news and weblog search engines were built in-house. The web search engine personalizes Google web search results.

When I search on Findory I have the option to search news, blogs, or the web. There does not seem to be an option to search a combination of those sources. As a user, I am less concerned about which source bucket the information comes from, than I am about the information itself. Any chance you might offer users an advanced search option to handle that? And how about advanced syntax?

It’s a great suggestion. We’ve designed our search engine to be simple, fast, and easy to use. So, while it is true that there are no advanced search options, the news, weblog, and web searches are quite unusual in that they are all personalized. Different users doing the same search on our site will see different search results, all depending on their history and their interests.

As an outsider looking in, and a user, my impression is that when I click on a link, Findory analyzes the keyword content of the site and looks for other sites with overlapping terms. Findory also does something like Amazon’s “Customers with similar searches also purchased…” functionality, except in this case it is “Other users who read this article also read…” I realize you are not able to give away the secrets of your technology, but what can you share with us about it?

At a high level, we look at what other readers like you are reading to recommend news stories to you. It’s a community. Imagine if friends of yours using Findory were constantly recommending articles to you. Now imagine that those friends are found automatically for you. That’s how Findory works.

How does Findory evaluate its personalized listings and search results in order to improve? In other words, is there any kind of testing or evaluation to determine the relevancy of the listings shown to users?

Great question. We’re constantly testing refinements to our algorithm and trying to improve on it. As we get more and more users of Findory, the quality of our recommendations get better and better. Findory builds on the strength of its community.

What subjects is Findory particularly good at surfacing for users? Any areas that need improvement?

The quality doesn’t seem to vary by subject, so I’m not sure this is a real issue for us. One area where we are seeking to improve is our weblog coverage. We have thousands of weblogs in our database, but that represents just a small fraction of the weblog content out there. We are working aggressively to extend our crawl.

Sometimes I want to be able to give feedback to the Findory engine when a site is not relevant. For example, I searched for San Francisco because as a San Franciscan I thought I would help Findory by focusing it on my location. However, the next time I used Findory there was an article about the San Francisco 49ers firing their head coach. And the next time I went back the lead article was about the NFL. In that case, Findory was close with the 49ers article, but in the end it was not relevant because I am not a football fan. Any plans to offer this kind of feedback loop?

It’s a great idea. We’re considering customization features such as being able to rate articles or sources or being able to say “not interested” on articles. We are looking at ways to do this that don’t interfere with the main purpose of Findory, reading news.

Do you see a way for regular search engines to integrate your technology?

Absolutely. Our technology is designed to be highly scalable. Despite our complicated personalization, the online portion of our processing only takes a tens of milliseconds. We want Findory’s personalization to be helping millions of readers find the information they need.

Blog searching by companies like Findory, Daypop, and Technorati, to name just a few, has become one of the hot search topics these days. How do you see blog searching fitting into the overall search engine industry in the next year or two? What about real-time indexing?

The real issue with weblogs is finding good content. Weblogs are self-published. No publisher means no filter. That’s a good thing and a bad thing. It’s good because it opens the floodgates for so much new content. It’s bad because those filters are sometimes useful, helping readers differentiate useful from useless. This problem will only get worse and worse as the blogging phenomenon accelerates.

Findory is all about relevance. In a sea of information, how do you surface what people need? Current web and weblog search engines all use the same relevance rank for all searchers, but not everyone has the same definition of relevance. Findory learns your interests — what is relevant for you — and surfaces that content.

Some have said 2005 will be the year search becomes personal. Findory has already taken the first steps.

I have yet to see a sponsored result or any banner ad on Findory. Would you mind commenting about Findory’s business model?

Findory currently has no advertising. We have designed a personalized advertising engine that targets based on reader’s interests, much like Google AdWords but more targeted. But, readers aren’t huge fans of advertising. At this point, we prefer to work on features our readers want. When we need to launch advertising to support our website, we’ll be ready.

Lastly, what’s your favorite drink?

Favorite drink? It’d have to be coffee. Caffeine is what keeps us geeks going.

Thanks Greg. Are there any other comments you’d like to add?

Thanks, Chris! Glad to hear you’re enjoying Findory!

Posted in: General, Interviews

Post Navigation

← Older Posts