Using contextual information to understand searching and browsing behavior

There is great imbalance in the richness of information on the web and the succinctness and poverty of search requests of web users, making their queries only a partial description of the underlying complex information needs. Finding ways to better leverage contextual information and make search context-aware holds the promise to dramatically improve the search experience of users. We conducted a series of studies to discover, model and utilize contextual information in order to understand and improve users' searching and browsing behavior on the web. Our results capture important aspects of context under the realistic conditions of different online search services, aiming to ensure that our scientific insights and solutions transfer to the operational settings of real world applications

A Survey on Automatically Mining Facets for Web Queries

In this paper, a detailed survey on different facet mining techniques, their advantages and disadvantages is carried out. Facets are any word or phrase which summarize an important aspect about the web query. Researchers proposed different efficient techniques which improves the user’s web query search experiences magnificently. Users are happy when they find the relevant information to their query in the top results. The objectives of their research are: (1) To present automated solution to derive the query facets by analyzing the text query; (2) To create taxonomy of query refinement strategies for efficient results; and (3) To personalize search according to user interest

A Comparative Analysis of Web Search Query: Informational Vs. Navigational Queries

The search engines are mainly used to retrieve relevant information. Information retrieval researchers show that queries are the basis for providing better search engine performance. The search query is becoming a means for users to search for their needed information. Web search query is one of the common search queries that is widely used in domain areas. However, the main challenge is the absence of a clear understanding of how web search query influences the users’ behavior on different web search engines. With the emergence of different types of a web search query, the understanding of user behavior on a web search query guides in improving the performance of many web search engines. Current research focused on using informational queries to search relevance information from a database while ignoring the importance of navigational queries. In this paper, we compared the informational and navigational type of a web search query that is mostly used in academic settings. Specifically, we examine the problems, solutions and techniques used in each of these types. We used a query log to conduct an experiment using BM25 mathematical model. The results indicated that the informational search query performed best because several keywords have been included to properly explain the queries. Also, language vocabularies used in informational queries contributed to better search performance. We believed that the outcomes of our comparisons will guide web search engine developers on the right search query for their web search engines