Search engines are still the most important gates for information search in internet. In this regard, providing the best response in the shortest time possible to the user's request is still desired. Normally, search engines are designed for adults and few policies have been employed considering teen users. Teen users are more biased in clicking the results list than are adult users. This leads...

Query recommendation suggests related queries for search engine users when they are not satisfied with the results of an initial input query, thus assisting users in improving search quality. Conventional approaches to query recommendation have been focused on expanding a query by terms extracted from various information sources such as a thesaurus like WordNet, the top ranked documents and so ...

Query recommendation has been recognized as an important tool that helps users in their information seeking activities. Many existing approaches leveraged the rich Web query logs to generate query recommendations. Recently, the query-flow graph, an aggregated representation of session information in query logs, has shown its utility in query recommendation. However, there are two major problems...

Query recommendation is considered an effective assistant in enhancing keyword based queries in search engines and Web search software. Conventional approach to query recommendation has been focused on query-term based analysis over the user access logs. In this paper, we argue that utilizing the connectivity of a query-URL bipartite graph to recommend relevant queries can significantly improve...

For a search engine, the challenge of finding relevant information from the web is becoming more and more difficult with rapid increase/change in content of the web. This difficulty further increases as queries submitted by users are general, imprecise, short and ambiguous. Relevance between user’s information need and documents returned by search engine is largely dependent on the query given ...

Query recommendation can not only effectively facilitate users to obtain their desired information but also increase ads’ click-through rates. This paper presents a general and highly efficient method for query recommendation. Given query sessions, we automatically generate many similar and dissimilar query-pairs as the prior knowledge. Then we learn a transformation from the prior knowledge to...