Expert Systems & Personalized Recommendations

September 27, 2007

Where is the web going? In an interesting post by Steven Spalding, How to Define Web 3.0, he discusses many trends of the web that are taking place right now and how he thinks they will evolve in the near future.

According to Steven, a user will start his/her journey on the web with one of three tasks – seeking information, seeking validation, or seeking entertainment. The word journey here implies a quest the user embarks on to find new information on the web (hence, this does not include activities such as email, chatting, etc which are increasingly become more integrated into the web). I want to point out the difference he makes between seeking information and seeking validation. He describes seeking information as essentially how we search online today – using search engines to find specific information via keywords. His definition for seeking validation is as follows:

“If I am not necessarily looking for information, but instead am looking for “news” (I use news in as loose a fashion as I can) the way I would use search would be slightly different. Along with the specialized search engines, People Search would be available. You could type in what you were looking for, “conservative viewpoint on Darwin” for example and it would pull up results ordered by relevance (algorithms), tagging, and validation through user voting.”

Here “news” can be extended to seeking opinions on various topics, finding what people are reading or blogging on a given subject, or researching trends. This is primarily a mode of casual information discovery using these “specialized search engines” mentioned that aggregate relationships between objects and people. Given that the nature of this information is inherently “peopled-driven”, it must largely be derived from the “wisdom of the crowds”. There is therefore an undeniable need to aggregate all such information (i.e. tagged, voted, commented information) and their relationships (quantitatively) and make it accessible to everyone on a very on-demand and contextually relevant basis.

Steven further makes an interesting prediction in regards to “Expert Systems” (which he defines as systems containing subject-specific information and the knowledge and analytical skills of one or more human experts):

“Ten years from now, Expert Systems won’t only be designed for general cases, but will be able to be easily generated to understand individual’s tastes. Already we see contextual advertising and contextual search, but what if you could extend this concept to a web browser or to your mobile phone. Imagine a world where your computer would generate a profile, a meme map about you based on your interactions with the web and refine your experience based on this map.

This is precisely what we are working to accomplish at Youlicit. Our vision is to create a Youlicit community of users and model dynamic interest maps of a user based on his online interactions with the web. This includes looking at explicit recommendations made by the User as well analyzing browsing patterns (if he so chooses) to create such a meme map. We can then use this information to create time-sliced profiles of the user and connect him to other users and relevant content on the web based on this interest map. Picture doing research on where to look for financial aid for college and being lead instantly not only to very relevant content (eg. graduate vs. undergraduate financial aid) that matches your current interest profile but also to users who have expressed strong interests in the college application process and various financial aid sites and have an abundance of relevant and seminal data that you can access. Or better yet, being able to reach out to these users (if they so choose) and communicating directly with them to leverage their expertise. This can all be possible with the wealth of information already present on the web and the evolution of the web from a relatively passive medium to a very dynamic, interactive, collaborative platform. What is needed is a tool to aggregate & analyze this information and provide it to the masses in an effortless, easy-to-use manner.


We’re back…

September 17, 2007

… and darker than before. The team just returned from a relaxing yet productive weekend in Orlando and Tampa. After spending endless hours on the beach and in the pool, we’re back in good ol’ New York. See below for some pictures:

Team Retreat – Orlando!

September 13, 2007

The Youlicit Team is taking a much needed weekend retreat to the sunshine state! We’ll be in Orlando for the weekend for some fun in the sun and the chance to do some serious thinking about our direction (and by serious thinking I mean brainstorming on Space Mountain). Stay tuned for some pictures of the weekend…

Search vs. Recommendations

September 12, 2007

In an interesting blog entry by Seth Godin, he states:

“The fact is that search engines are very good at fairly simple searches, and very good at finding information about single products, services, people and ideas. But they’re terrible at connections, at rankings, at horizontal results… They can’t help me find six products that are viable alternatives to something that was just discontinued.”

These are precisely the problems we are trying to address at Youlicit. Our primary focus is drawing connections between horizontal results, or to put it more plainly providing “recommendations” on topics, through user provided data.

While Google and Yahoo! are “search” engines, Youlicit is a “recommendation” engine.

What’s the difference between search and recommendations you ask? Search is when you precisely know what you are looking for, whereas recommendations are when you aren’t entirely sure and would like some guidance on where to go and what to see. A great example is visiting your local department store. Search is the equivalent of going to the store and saying, “I’m looking for a navy blue dress shirt with thin vertical stripes.” Recommendations are when you walk to the mens department, pick up a blue shirt and say, “Can you show me more like this?”

As applied to web content, when you can accurately guess the keywords that are likely to occur on the pages you’re looking for, use search. But when you’re not quite sure how to describe what you’re looking, but you know it’s related to what you’re currently looking at, that’s when you Youlicit More recommmendations!

Youlicit – Just keeps getting better!

September 12, 2007

As some of you may have already noticed, we gave our front page an overhaul. Part of the reasoning for this was that the original look was too “Google-y” and we wanted to try and steer away from coming off as a traditional search engine. We are not a traditional search engine. Hence the new look was created to help show you guys at a glance our value prop, how we work and why you should care.

In addition to this, we completely re-did our back end to make it work a couple of orders of magnitude faster!! You can now enjoy Youlicit’s great results faster than you can say “Wow!”. (Some of our older user’s may notice that we arent supporting tagged-based searching – we are still upgrading that functionality to the new technology and should have that back up for you soon).

We have also released a new and updated toolbar! If you still have the older version of the toolbar, please update it with the new release. Some of the functionality includes: Light up features to denote that there are recommendations for the given site you are on, an updated “Recommend” or A-Ok button that lights up to denote that you have recommended the site you are on.

Also, Digg users, now you can upload your recently dugg sites into Youlicit to jump start your experience here – get personalized recommendations on them, a user profile and find users with similar interests! Just navigate to your settings page (requires registration) and upload away!

As always, we love to hear from you so please feel free to provide us feedback, criticism or love (and don’t hold back).

– The Youlicit Team