A Survey on Location-Aware Keyword Query Suggestion Based On Document Proximity

Keyword suggestion in web search is a very important feature to be considered in today’s growing world. It helps user to access the information without any prior knowledge of how to express in queries. The main concept of query suggestion is used to retrieve documents from the related server by consuming less time. Platform is provided by search engines for users to describe their information need more precisely by using query recommendation. Previously there has been lot of work done for retrieving relevant data of users to meet their information need and improving performance of search engines. This paper reviews and compares different available methods in query log processing for information retrieval. Then conclude that Existing keyword suggestion techniques are not considering the locations of the users and the query results which serves as a drawback of existing systems. The spatial factor is not considered to retrieve result. The approach based on location aware keyword query suggestion is better to understand user’s interaction process with search engines to find the appropriate information need.

Web mining is the application of data mining techniques to extract knowledge from web data, including web documents, hyperlinks between documents, etc. Mining in such a hug data is very difficult. User issuing query is in need of information related to his query and providing user with data of his interest is very important task. Users’ needs are to get the relevant documents related to its search query so that less amount of time is invested for searching. Nowadays, query suggestion is the important factor that cannot be ignored. End user inputs the query, and expect the intelligent search engines to suggest relevant results as per end users need. Sometimes end user fails to express relevant query which may lead to unsatisfactory results. Hence, there comes a need to develop a model that consider such problems. Even if the results are relevant they are not nearer to end users location. Location based retrieval is as important as relevant information. There are various existing methods that do not consider user’s location while retrieving the query results. There is need to not only retrieve documents related to the user information needs but also located near the user location.

Due to the emerging use of search engine it is very important to provide best results to the end user of the search engine. There are number of techniques that are currently being used to retrieve relevant documents according to query issuer’s interest. When issuer issues a query, crawler of the engine crawls to fetch relevant documents according to the query and return it back to the user or query issuer. After submitting a keyword query, the user may not be satisfied with the results, so the keyword suggestion module of the search engine recommends a set of m keyword queries that are most likely to refine the users search in the right direction. Many times query issuer requires the search results nearby their current location. This requirement is of location based document retrieval is not made available in existing techniques. Hence, Location based Keyword search is studied so that query issuer is provided with location based results. Hence, we have presented a Location-aware keyword query suggestion frame work that provides relevant keyword suggestion to the user and at the same time can retrieve location based documents which improves the quality of keyword suggestion.

Main focus – Data mining, spatial location, keyword suggestion.