Sensual Semantic Analysis for Effective Query Expansion
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2018, Vol 9, Issue 12
Abstract
The information has evolved rapidly over the World Wide Web in the past few years. To satisfy information needs, users mostly submit a query via traditional search engines, which retrieve results on the basis of keyword matching principle. However, a keyword-based search cannot recognize the meanings of keywords and the semantic relationship among the terms in the user’s query; thus, this technique cannot retrieve satisfactory results. The expansion of an initial query with relevant meaningful terms can solve this issue and enhance information retrieval. Generally, query expansion methods consider concepts that are semantically related to query terms within the ontology as candidates in expanding the initial query. An analysis of the correct sense of query terms, rather than only considering semantic relations, is necessary to overcome language ambiguity problems. In this work, we proposed a query expansion framework on the basis of query sense analysis and semantics mining using computer science domain ontology, followed by working prototype of the system. The experts analyzed the results of system prototype over test dataset and Web data, and found a remarkable improvement in the overall search performance. Furthermore, the proposed framework demonstrated better mean average precision and recall values than the baseline method.
Authors and Affiliations
Muhammad Ahsan Raza, M. Rahmah, A. Noraziah, Mahmood Ashraf
Keywords
Related Articles
- EP ID EP429107
- DOI 10.14569/IJACSA.2018.091208
- Views 83
- Downloads 0
Graduation Certificate Verification Model: A Preliminary Study
Graduation certificates issued by universities and other educational institutions are one of the most important documents for a graduate. It is a proof of graduate’s qualifications and can be used to advance forward in o...
Clustering of Image Data Using K-Means and Fuzzy K-Means
Clustering is a major technique used for grouping of numerical and image data in data mining and image processing applications. Clustering makes the job of image retrieval easy by finding the images as similar as given i...
A Framework for Creating a Distributed Rendering Environment on the Compute Clusters
This paper discusses the deployment of existing render farm manager in a typical compute cluster environment such as a university. Usually, both a render farm and a compute cluster use different queue managers and assume...
The Use of a Simplex Method with an Artificial basis in Modeling of Flour Mixtures for Bakery Products
Modeling of flour mixtures for bakery products of increased biological value is done. The problem is solved by a simplex method with an artificial basis related to numerical optimization methods for solving linear progra...
Investigate the Performance of Document Clustering Approach Based on Association Rules Mining
The challenges of the standard clustering methods and the weaknesses of Apriori algorithm in frequent termset clustering formulate the goal of our research. Based on Association Rules Mining, an efficient approach for We...