Improving Faceted Search Results for Web-based Information Exploration

Mohammed Najah Mahdi, Abdul Rahim Ahmad, Roslan Ismail

Abstract


The World Wide Web (WWW), a fast-growing store, contains a significant portion of human knowledge. However, the sheer scale of the Web, along with the fact that it is decentralized, highly redundant, and largely inaccurate, causes the use of the knowledge is quite cumbersome. The present search engines (SEs) use the query, and the response lookup process is incapable of producing a precise result. Thus, researchers work beyond this paradigm to explore a new class of methods to seek information, which known as an exploratory search (ES). This ES is open-ended, and its faceted search (FS) improves the overall search process. The search engine presented in this study is running in the cloud computing platform environment. Its development is based on the idea of improving visual ES while exploring information on the Web. This notion reflects the process of seeking and combing the vast information by using the coordinated visualization method, apart from minimizing the effort spent in seeking information per query. Finally, we evaluate the proposed prototype against the Internet Movie Database (IMDb) search engine, an online database of information related to films, television programs, home videos, video games, and streaming content online including cast, production crew, and personal biographies, plot summaries, trivia, fan, and critical reviews, and ratings.  The results show that the proposed search engine gives more relevant search results as compared with the others.

Keywords


exploratory search; faceted search; visualization; search engine.

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References


M. d. Kunder, "World Wide Web Size. ," https://www.worldwidewebsize.com/, 2016.

J. Curran, N. Fenton, and D. Freedman, Misunderstanding the internet: Routledge, 2016.

A. Selcuk, C. Örencik, and E. Savas, "Private search over big data leveraging distributed file system and parallel processing," 2015.

S. M. Y. Esbitan, "A Personalized Context-Dependent Web Search Engine Using Word Net (Sama Search Engine)," A Personalized Context-Dependent Web Search Engine Using Word Net (Sama Search Engine), 2012.

H. Wachsmuth, M. Potthast, K. Al Khatib, Y. Ajjour, J. Puschmann, J. Qu, et al., "Building an argument search engine for the web," in Proceedings of the 4th Workshop on Argument Mining, 2017, pp. 49-59.

M. N. Mahdi, A. R. Ahmad, and R. Ismail, "A Real Time Visual Exploratory Search Engine for Information Retrieval in a Cloud," International Journal of Future Computer and Communication, vol. 4, p. 216, 2015.

K. Collins-Thompson, S. Y. Rieh, C. C. Haynes, and R. Syed, "Assessing learning outcomes in web search: A comparison of tasks and query strategies," in Proceedings of the 2016 ACM on Conference on Human Information Interaction and Retrieval, 2016, pp. 163-172.

M. Dörk, "Visualization for Search: Exploring Complex and Dynamic Information Spaces," Doctoral dissertation, University of Calgary, 2012.

G. Marchionini, "Exploratory search: from finding to understanding," Communications of the ACM, vol. 49, pp. 41-46, 2006.

D. Sonntag and H.-J. Profitlich, "An architecture of open-source tools to combine textual information extraction, faceted search and information visualisation," Artificial intelligence in medicine, vol. 93, pp. 13-28, 2019.

M. Breeding, "We need to go beyond Web 2.0," Computers in libraries, vol. 27, pp. 22-25, 2007.

E. Gorelik, "Cloud computing models," Doctoral dissertation, Doctoral dissertation, Massachusetts Institute of Technology, 2013.

B. R. Prasad and S. Agarwal, "Comparative Study of Big Data Computing and Storage Tools: A Review," International Journal of Database Theory and Application, vol. 9, pp. 45-66, 2016.

H. Al-Aqrabi, L. Liu, R. Hill, L. Cui, and J. Li, "Faceted Search in Business Intelligence on the Cloud," in Green Computing and Communications (GreenCom), 2013 IEEE and Internet of Things (iThings/CPSCom), IEEE International Conference on and IEEE Cyber, Physical and Social Computing, 2013, pp. 842-849.

M. Bastian, S. Heymann, and M. Jacomy, "Gephi: an open source software for exploring and manipulating networks," in Third international AAAI conference on weblogs and social media, 2009.

M. Card, Readings in information visualization: using vision to think: Morgan Kaufmann, 1999.

R. Spence, Information visualization vol. 1: Springer, 2001.

S. Hadlak, H. Schumann, and H.-J. Schulz, "A survey of multi-faceted graph visualization," in Eurographics Conference on Visualization (EuroVis), 2015, pp. 1-20.

W. Dakka, R. Dayal, and P. G. Ipeirotis, "Automatic discovery of useful facet terms," in SIGIR Faceted Search Workshop, 2006, pp. 18-22.

W. Kong, "Extending Faceted Search to the Open-Domain Web," University of Massachusetts Libraries, 2016.

M. N. Mahdi, A. R. Ahmad, and R. Ismail, "Paradigm Extension of Faceted Search Techniques A Review," Journal of Telecommunication, Electronic and Computer Engineering (JTEC), vol. 9, pp. 149-153, 2017.

R. W. White and R. A. Roth, "Exploratory search: beyond the query-response paradigm (Synthesis lectures on information concepts, retrieval & services)," Morgan and Claypool Publishers, vol. 3, 2009.

W.-C. Lin, S.-W. Ke, and C.-F. Tsai, "SAFQuery: a simple and flexible advanced Web search interface," The Electronic Library, vol. 34, pp. 155-168, 2016.

C. Costa and M. Y. Santos, "Big Data: State-of-the-art concepts, techniques, technologies, modeling approaches and research challenges," IAENG International Journal of Computer Science, vol. 43, pp. 285-301, 2017.

H. Cui, J.-R. Wen, J.-Y. Nie, and W.-Y. Ma, "Query expansion for short queries by mining user logs," IEEE Trans. Knowl. Data Eng, vol. 15, pp. 829-839, 2002.

J. Teevan, E. Adar, R. Jones, and M. A. Potts, "Information re-retrieval: repeat queries in Yahoo's logs," in Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval, 2007, pp. 151-158.

R. W. White and S. M. Drucker, "Investigating behavioral variability in web search," in Proceedings of the 16th international conference on World Wide Web, 2007, pp. 21-30.

N. Dalum Hansen, K. Mølbak, I. J. Cox, and C. Lioma, "Seasonal Web Search Query Selection for Influenza-Like Illness (ILI) Estimation," in Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2017, pp. 1197-1200.

C. Ahlberg, C. Williamson, and B. Shneiderman, "Dynamic queries for information exploration: An implementation and evaluation," in Proceedings of the SIGCHI conference on Human factors in computing systems, 1992, pp. 619-626.

D. R. Harris, "Modeling Integration and Reuse of Heterogeneous Terminologies in Faceted Browsing Systems," in Information Reuse and Integration (IRI), 2016 IEEE 17th International Conference on, 2016, pp. 58-66.

C. Di Sciascio, P. Brusilovsky, and E. Veas, "A Study on User-Controllable Social Exploratory Search," in 23rd International Conference on Intelligent User Interfaces, 2018, pp. 353-364.

J.-W. Ahn and P. Brusilovsky, "Adaptive visualization for exploratory information retrieval," Information Processing & Management, vol. 49, pp. 1139-1164, 2013.

R. Beecham, C. Rooney, S. Meier, J. Dykes, A. Slingsby, C. Turkay, et al., "Faceted Views of Varying Emphasis (FaVVEs): a framework for visualising multi‐perspective small multiples," in Computer Graphics Forum, 2016, pp. 241-249.

V. T. Lee, A. Mazumdar, C. C. del Mundo, A. Alaghi, L. Ceze, and M. Oskin, "POSTER: Application-Driven Near-Data Processing for Similarity Search," in Parallel Architectures and Compilation Techniques (PACT), 2017 26th International Conference on, 2017, pp. 132-133.

L. Chen, Y. Gao, X. Li, C. S. Jensen, and G. Chen, "Efficient Metric Indexing for Similarity Search and Similarity Joins," IEEE Transactions on Knowledge and Data Engineering, vol. 29, pp. 556-571, 2017.

A. Jain, N. Lupfer, Y. Qu, R. Linder, A. Kerne, and S. M. Smith, "Evaluating TweetBubble with ideation metrics of exploratory browsing," in Proceedings of the 2015 ACM SIGCHI Conference on Creativity and Cognition, 2015, pp. 53-62.

H. C. L. Hsieh and N. C. Cheng, "A Theoretical Model for the Design of Aesthetic Interaction," in International Conference on Human-Computer Interaction, 2016, pp. 178-187.

G. Kumar, "Top 10 search Engines List Learn more about them," 2016.

B. Kumar and S. Pavithra, "Evaluating the searching capabilities of search engines and metasearch engines: A comparative study," 2010.

Y. Luo, W. Wang, X. Lin, X. Zhou, J. Wang, and K. Li, "Spark2: Top-k keyword query in relational databases," IEEE Transactions on Knowledge and Data Engineering, vol. 23, pp. 1763-1780, 2011.

T. A. Usmani, D. Pant, and A. K. Bhatt, "A comparative study of google and bing search engines in context of precision and relative recall parameter," International Journal on Computer Science and Engineering, vol. 4, p. 21, 2012.

J. Uddin, S. M. Ahmad, S. U. Jan, and A. Reba, "Precision and Relative Recall of Search Engines using Education Keywords: A Comparative study of Google, Yahoo and Refseek," PUTAJ-Humanities and Social Sciences, vol. 25, pp. 99-112, 2017.

C. L. Smith, J. Gwizdka, and H. Feild, "Exploring the Use of Query Auto Completion: Search Behavior and Query Entry Profiles," in Proceedings of the 2016 ACM on Conference on Human Information Interaction and Retrieval, 2016, pp. 101-110.




DOI: http://dx.doi.org/10.18517/ijaseit.10.3.9959

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