文章基本信息

标题：A Review on Hybrid Approach for Searching and Ranking Large Scale Web Data using Social Media Factors
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作者：Prof. Yogesh Lonkar ; Dattatray Savant ; Prashant Nikam 等
期刊名称：International Journal of Innovative Research in Science, Engineering and Technology
印刷版ISSN：2347-6710
电子版ISSN：2319-8753
出版年度：2017
卷号：6
期号：11
页码：21854
DOI：10.15680/IJIRSET.2017.0611134
出版社：S&S Publications
摘要：In last few years, there has been a hard development of incorporating results starting structured datasource into keyword based web track systems such as Amazon as well as Google or any search engines. In searchengines, different users may seek for different information by issuing the similar query. To convince more users withpartial search results, search result diversification re-ranks the results to coat as many user intents as probable. Mostpresented intent-aware diversification algorithms differentiate user intentions as subtopics, every of which is typically aword, a phrase, or a piece of clarification. Web search queries are often uncertain or multi-search, which makes aeffortless ranked list of results insufficient. To help information finding for such queries, system explore a techniquethat explicitly represents fascinating meaning of a query using groups of semantically related terms retrieved fromsearch results. In the proposed work system denote a supervised approach based on a graphical model to identificationof web queries show that the supervised approach significantly outperforms existing methods, which are mostlyunsupervised, recommending that query facet retrieval can be effectively learned. First, the temporal prevalence of aparticular topic in the news media is a factor of importance, and can be considered the media focus of a topic. Second,the temporal prevalence of the topic in social media indicates its user attention. Last, the interaction between the socialmedia users who mention this topic indicates the strength of the community discussing it, and can be regarded as theuser interaction toward the topic. We propose an unsupervised framework approach which identifies any type of searchquery, and then ranks them by relevance using their weight as well as their number of visit by users.
关键词：Information Filtering; Social Computing; Social Network Analysis; Topic Identification; Topic;Ranking