Expert Systems & Personalized Recommendations

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.

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One Response to Expert Systems & Personalized Recommendations

  1. […] Richard McManus poses an almost rhetorical question on his blog entry asking if search and social networking go together. We believe that the purpose of a search tool is to help you find the information you need with the least effort possible (see Relevance/Effort metric). To this end, if there is someone who has, and is willing to share, the information or expertise you are looking for, then what better medium to connect you to him than that in which you already go to find your information. Granted there is a spectrum of modes that different users fall into depending on their personality types (and time constraints) ranging from solitary to the very social (as pointed out by Charles Knight in his blog).  In the end everyone can and wants to benefit from accessing the information (and people) they need as quickly as possible. This is why we are including “Related Users” for every query you perform on Youlicit (this feature is soon to come and can currently be seen on your Personalized Recommendations and User pages). We are using this as a base to build out a social networking aspect to our website recommendation service. As you read this, we are working hard to better determine what users are interested in as well as allow users to share with others what they are recommending on a certain topic. The end goal is to become an enabler of collaboration between users to better facilitate the discovery and sharing of information. Building a social network based on your real world relationships with people you already know can help improve and extract more value out of those relationships but isn’t the most effective means to introduce you to other people you ought to know. A higher value social network connects you to people who share your interests and can help you not only discover the information you need quicker but ultimately increase your productivity and introduce you to more “meaningful” resources in your area of interest (see Expert Systems entry). […]

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