Web Site Personalization By Learning User Profile

6482 words - 26 pages

Abstract In this paper we discuss a technique for web site personalization. Connectivity analysishas been shown to be useful in identifying high quality web pages within a topic or domainspecific graph of hyperlinked documents. The essence of our approach is to augment a previousconnectivity analysis with content analysis. We present an agent which assists the user when hebrowses and distills a personalized sub graph of the website based on his user profile.1 IntroductionThe Web is full of information and resources. The problem is that people have to spend a lot oftime and effort to navigate but may not find interesting personalized information [23]. In thisproject we present a personal agent that assists a user when he browses. Adaptive web pages helpthe user in finding relevant information by tailoring their content and layout specific to thevisiting user. Most web sites are designed with a "One size fits all" philosophy. The web sitedesigner designs a web site containing a particular user model in mind and then creates thecontent accordingly. However the visitors may use the site in ways unanticipated by the sitedesigner. For example, a site that contains a broad array of information such as a travelinformation site may be structured with as deep hierarchy according to countries, historical sites,tourist sites etc. However, visitors may follow only a few paths through this site, and the deephierarchy is needlessly burdensome. Also a user may like to visit the pages for all sea resortsdestinations, which require altering the clustering of documents while not altering the content ofeach page.Another motivation to develop such a system is for the users with poor Internet connectivity.Search engines often return top-level home pages, which do not have much of content, andinvariably a user needs to browse deeper to extract the relevant information. For example avillage school where the Internet access is for maximum one or two hours in a day and onlinebrowsing is not feasible due to slow connection. In such cases our system can be effectively usedto download the personalized sub graph of the website and browsed later in offline mode. Inaddition, a visitor's web client may be constrained in some way, perhaps by a small screen size orslow network connection. Content designed for large, colour displays and fast networks, isseldom useful for such constrained devices. One basic issue in implementation of such agents isits location. We propose this agent to be based on a caching proxy server.The paper is structured as follows. Section 2 describes the representational model that we haveused for representing the documents in our system. We will discuss the N-dimensional vectorspace model and stemming of words. Section 3 defines personalization and its needs. Section 4presents the details of the data structures used and also demonstrate the use of graph centricalgorithms in adapting a website and also discusses our core algorithm and how an adaptiveWeb Site...

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