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UQSCM-RFD:  A query–knowledge interfacing approach for diversified query recommendation in semantic search based on river flow dynamics and dynamic user interaction

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Abstract

Owing to the exponential intensification of the web information content and transfiguration of the conventional Web into a more sophisticated Semantic Web, there is a mandated need for semantics aware web recommendation systems. In this paper, a graph-based semantic strategy for query recommendation has been proposed. Firstly, the paper aims at the construction of the proposed Query Sense Concept Tripartite graph for the initially built Query Click Graph. Secondly, a novel river flow dynamics strategy has been proposed for the selection of the best concept entailment path for integrating real-world knowledge from semantic wikis. Thirdly, an adaptation of the Tversky Index with parametric variations for computing the semantic similarity further contributes to novelty. Finally, a horizontal–vertical grid-based dynamic capture of user intents has been proposed for understanding the current informational needs of the user. Experimentations have been conducted for both the AOL and the SIGIR datasets for computing the performance of the Query Recommendation. An accuracy of 0.86 and 0.91 has been achieved for the AOL and the SIGIR datasets with a very low FDR of 0.11 and 0.07, respectively, which is the best-in-class performance when benchmarked with the baseline methods.

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Acknowledgements

I thank God the Almighty and Eternal Father and my Lord Jesus Christ, the Most High and the Holy Spirit for granting me Knowledge and Wisdom to productively finish this work. I especially thank my parents and sister who stood by me during the implementation and the progress of this work.

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  1. Department of Computer Science and Engineering, National Institute of Technology, Tiruchirappalli, India

    Gerard Deepak & A. Santhanavijayan

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  1. Gerard Deepak
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  2. A. Santhanavijayan
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Correspondence to Gerard Deepak.

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Deepak, G., Santhanavijayan, A. UQSCM-RFD:  A query–knowledge interfacing approach for diversified query recommendation in semantic search based on river flow dynamics and dynamic user interaction. Neural Comput & Applic 34, 651–675 (2022). https://doi.org/10.1007/s00521-021-06404-w

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