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|Title: ||OPTIMUM WEB PERSONALIZATION SYSTEM USING SEMANTIC ANNOTATION|
|Keywords: ||web mining, web personalization, Semantic Annotation, user query, ecommerce, semantic similarity|
|Researcher: ||Sunny Sharma|
|Guide(s): ||Dr Vijay Rana (Co-Supervisor)|
|Registration Date: ||7-8-2017|
|Abstract: ||Due to excessive amount of information available on the Web, it is much tedious task to retrieve the information from the web. In this case, Web search Personalization plays a great role in both research and commercial areas. Anticipating the web user needs is one of the key factors of our research and provides the qualitative results based on web user behavior. If these needs are quickly recognized, the customer can be offered the best products instantly. E-commerce search engines usually provide search results without considering user context or interests. Ecommerce web search personalization is an emerging area in the research which has already been achieved the curiosity. In our research; we proposed an approach for personalizing the web search using techniques, applications and opportunities of Data mining and web mining. Moreover we also use the process of annotating the documents which helps to make the information machine understandable. In the Web domain, it is achieved by gathering prominent information specific to each user, either implicitly or explicitly. A user s profile contains information about the user, his interests and even his behavior while surfing a Web site. This information is exploited in order to personalize the contents of a Web site to the specific visitors and individual needs. Semantic annotations are the some Meta descriptions known as meta- tags used on the web which helps to make the information machine understandable. Integrating tagging information can assist to advance personalization and retrieval techniques. The whole process of personalization involves data collection and preprocessing phase in which the information pertaining to user interests is collected and preprocessed and a discovery phase in which user profiles are constructed from the data collected and results are provided to the user.
|Appears in Department:||Department of Computer Science Application|
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