Query recommendation based on query relevance graph

Sejal, D. and Shailesh, K.G. and Tejaswi, V. and Venugopal, K.R. and Dinesh Anvekar, . and Iyengar, S.S. and Patnaik, L.M. (2016) Query recommendation based on query relevance graph. Transactions on Machine Learning and Data Mining, 9 (1). pp. 3-26.

Full text not available from this repository.
Official URL: http://10.1109/TENSYMP.2015.22


With the explosive and diverse growth of web contents, query recommendation is a critical aspect of the search engine. Different kind of recommendation like query, image, movie, music and book etc. are used every day. Different kinds of data are used for the recommendations. If we model the data into various kinds of graphs then we can build a general method for any recommendation. This paper presents a general method to recommend queries by combining two graphs: 1) query click graph which uses the knowledge of link between user input query and clicked URLs and 2) query text similarity graph which finds the similarity between two queries using Jaccard similarity. The proposed method provides literally as well as semantically relevant queries for users’ need. Experiment results show that the proposed algorithm outperforms heat diffusion method by providing more number of relevant queries. It is also …

Item Type: Article
Uncontrolled Keywords: Heating , Java , Search engines , Bipartite graph , Uniform resource locators , Algorithm design and analysis , Semantics
Subjects: Faculty of Engineering > Computer Science & Information Science Engineering
Divisions: University Visvesvarayya College of Engineering > Department of Computer Science and Information Science Engineering
Depositing User: Ms Laxmi Kamble
Date Deposited: 16 Sep 2021 11:27
Last Modified: 16 Sep 2021 11:27
URI: http://eprints-bangaloreuniversity.in/id/eprint/9658

Actions (login required)

View Item View Item