As web contents grow, the importance of search engines become more critical and at the same time user satisfaction decreases. Query recommendation is a new approach to improve search results in web. In this paper a method is proposed that, given a query submitted to a search engine, suggests a list of queries that are related to the user input query. The related queries are based on previously ...

In this work, the authors address the problem of finding desirable and accurate information on the web by search engines due to two problems of low precision and low recall caused by significant and rapid growth in amount of information and the number of users. Based on the studies performed on query recommendation system using keyword extraction from the search results for a query, an algorith...

With the prevalence of mobile search nowadays, the benefits of mobile query recommendation are well recognized, which provide formulated queries sticking to users’ search intent. In this paper, we introduce the problem of query recommendation on mobile devices and model the user-location-query relations with a tensor representation. Unlike previous studies based on tensor decomposition, we stud...

We present a method to help a user redefine a query suggesting a list of similar queries. The method proposed is based on clickthrough data were sets of similar queries could be identified. Scientific literature shows that similar queries are useful for the identification of different information needs behind a query. Unlike most previous work, in this paper we are focused on the discovery of b...

The most commercial search engines return the search list by matching the user query terms with the documents available in its database. The relative effectiveness of search list is highly affected by the extent to which the query keywords map to the actual need of user. User generally forms the short, ambiguous and instant queries which lead to inclusion of irrelevant documents in the search l...

Recommendation techniques is now a day’s very important. various kinds of recommendations are done on the Web, example movies, music, images, books recommendations, query suggestions and tags recommendations, etc. it is not important that what kind of data sources are used for the recommendations, these data sources can be modeled or taken in the various types of graphs. In this paper, We are d...

Knowledge representations have greatly enhanced the fundamental human problem of information search, profoundly changing representations of queries and database information for various retrieval tasks. Despite new technologies, little thought has been given in the field of query recommendation – recommending keyword queries to end users – to a holistic approach that recommends constructed queri...

The increased availability of large amounts of data about user search behaviour in search engines has triggered a lot of research in recent years. This includes developing machine learning methods to build knowledge structures that could be exploited for a number of tasks such as query recommendation. Query flow graphs are a successful example of these structures, they are generated from the se...