Archive for May, 2006

Partnership of Yahoo and EBay

May 25, 2006 at 11:36 am · Filed under Web2.0

In industry, news of partnership of Yahoo and eBay boost the share prices of both companies. Many people think it is a win-win situation. I think so too. Both eBay and Yahoo! really need some good news to boost the confidence of investors. Google is eating away the search share of Yahoo. GBuy and Google Base are threats to eBay and Paypal.

From the technology perspective, Yahoo now forwards in the social media direction. For Yahoo, one potentially advantage of partnering with eBay is the huge user base of eBay. Moreover, many eBay users are very serious and loyal. Like MySpace and Facebook, Yahoo can build a big social network based on shoppers and businessmen of eBay. Yahoo can provide the personalized search and recommendation system service to the eBay users.

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Personalization and Web 2.0

May 22, 2006 at 11:57 am · Filed under Web2.0

Web 2.0 is hot. O’Reilly believes that one important feature of Web 2.0 is collective intelligence.  I consider the collective intelligence as the same thing as manpower or mass collaboration.

Does Personalization belong to Web 2.0? In my opinion, it does not in the narrow sense since the personalization technology does not necessarily utilize collective intelligence. However, personalization is strongly related with recommendation systems, collaborative filtering and social network, which belong to Web 2.0. Thus it belongs to Web 2.0 in the broad sense.

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PIM Workshop of SIGIR 2006

May 21, 2006 at 11:00 am · Filed under SIGIR, UCAIR, personal information management

At SIGIR 2006, there is a two-day workshop about Personal Information Management (PIM). We submit a paper about capturing and exploiting personal search history to improve retrieval accuracy. Here is the abstract of the submission.

Personal search history is an important type of personal information that is critical for learning a user’s interests and information needs and can be exploited to improve the search service for a user. In this paper, we describe our recent work on User-Centered Adaptive Information Retrieval (UCAIR), which aims at capturing personal search history with a client-side search agent and exploiting the history information to help a user optimize search results.

   

We propose a decision theoretic framework and develop techniques for implicit user modeling based on a user’s personal search history.  We propose several context-sensitive retrieval algorithms based on statistical language models to combine the personal search history with the current query for better ranking of documents. Using these techniques, we have developed an intelligent client-side web search agent, i.e., the UCAIR search agent, which can automatically capture a user’s personal search history, store it in XML format on the local disk, and exploit it to provide personalized search.

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