Semantic Web user personalization and search techniques based on time and weather condition
R. Kousalya, Sri Venkateshwara · 2014
As a result of the rapid advancements in Information Technology, Information Retrieval on Internet is gaining importance, day by day. The web comprises of huge amount of data and search engines provide an efficient way to help navigate the web and get the relevant information. General search engines, however, return query results without considering user's intention behind the query. Personalized Web search is carried out for information retrieval for each user incorporating his/her interests. This paper presents a method which extracts the user's interests and preferences of content according to weather and time. Also it calculates the semantic relativity between the given words, and it will generate the semantic measures automatically. The result shows that the model built with user preferences by time-framed navigation sessions improve the effectiveness of personalization process.