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Semantic Web Mining of Un-structured Data: Challenges and Opportunities
Manoj Manuja, Deepak Garg
Pages - 268 - 276 | Revised - 01-07-2011 | Published - 05-08-2011
Published in International Journal of Engineering (IJE)
MORE INFORMATION
KEYWORDS
Semantic Web, Web Mining, Unstructured Data
ABSTRACT
The management of unstructured data is acknowledged as one of the most critical unsolved problems in data management and business intelligence fields in current times. The major reason for this unresolved problem is primarily because of the actuality that the methods, systems and related tools that have established themselves so successfully converting structured information into business intelligence, simply are ineffective when we try to implement the same on unstructured information. New methods and approaches are very much necessary. It is a known realism that huge amount of information is shared by the organizations across the world over the web. It is, however, significant to observe that this information explosion across the globe has resulted in opening a lot of new avenues to create tools for data management and business intelligence primarily focusing on unstructured data. In this paper, we explore the challenges being faced by information system developers during mining of unstructured data in the context of semantic web and web mining. Opportunities in the wake of these challenges are discussed towards the end of the paper.
1 | Pandey, S. R., & Panda, K. C. (2015). Semantic solutions for the digital libraries based on semantic web technologies. Annals of Library and Information Studies (ALIS), 61(4), 286-293. |
2 | Malik, K. R., Ahmad, T., Farhan, M., Aslam, M., Jabbar, S., Khalid, S., & Kim, M. (2015). Big-data: transformation from heterogeneous data to semantically-enriched simplified data. Multimedia Tools and Applications, 1-21. |
3 | Geetharani, S., & Priyadharshini, S. (2015). A Survey on Web Usage Mining. International Journal of Emerging Trends in Science and Technology, 2(03). |
4 | Piña, C. R. R., Aguilar, J. L., Cerrada, M., & Altamiranda, J. Integración de Ontologías desde el punto de vista de Minería Ontológica y del Paradigma de Arquitecturas Orientadas a Servicios. |
5 | LAMPI, J. (2014). Large-Scale Distributed Data Management and Processing Using R, Hadoop and MapReduce. University of Oulu, Department of Computer Science and Engineering. Master's Thesis. |
6 | Polpinij, J. (2014). Ontology-based knowledge discovery from unstructured and semi-structured text. |
7 | Rana, V., & Singh, G. (2014, November). Analysis of web mining technology and their impact on semantic web. In Computational Intelligence on Power, Energy and Controls with their impact on Humanity (CIPECH), 2014 Innovative Applications of (pp. 5-11). IEEE. |
8 | Kontiza, K., & Bikakis, A. (2014, June). Web Search Results Visualization: Evaluation of Two Semantic Search Engines. In Proceedings of the 4th International Conference on Web Intelligence, Mining and Semantics (WIMS14) (p. 39). ACM. |
9 | Geeta, R. B., Totad, S. G., & Reddy, P. P. (2014, January). Web Site Reorganization Based on Topology and Usage Patterns. In Proceedings of the Second International Conference on Soft Computing for Problem Solving (SocProS 2012), December 28-30, 2012 (pp. 841-848). Springer India. |
10 | Polpinij, J. (2013). Ontology-based Knowledge Discovery from Unstructured Text. International Journal of Information Processing and Management, 4(4), 21. |
11 | Thakare, P. D., Ghonge, M., Gupta, S., Bhosle, A. A., Raich, A. R., Vidhate, A., ... & Kadam, S. U. (2013). A REVIEW ON INFORMATION REPRESENTAION AND RETRIVAL IN SEMANTIC WEB. |
12 | Nithish, R., Sabarish, S., Kishen, M. N., Abirami, A. M., & Askarunisa, A. (2013, December). An ontology based sentiment analysis for mobile products using tweets. In Advanced Computing (ICoAC), 2013 Fifth International Conference on (pp. 342-347). IEEE. |
13 | Bharamagoudar, G. R., Totad, S. G., & PVGD, P. R. Literature Survey on Web Mining. IOSR Journal of Computer Engineering (IOSRJCE) ISSN: 2278-0661, ISBN: 2278-8727 Volume, 5, 31-36. |
14 | Awad, A., El-Sayed, M., & El-Sonbaty, Y. (2012). Approximating User's Intention for Search Engine Queries. In WEBIST (pp. 422-425). |
15 | Madhak, N. N., Chauhan, S. G., & Varnagar, C. R. Understanding the Scope of Web Mining-Comprehensive Study. In National Conference on Emerging Trends in Computer & Electrical Engineering. |
A Maedche. (2002). “Ontology Learning for the Semantic Web”; Kluwer. ISBN: 0792376560 | |
A. Doan, R. Ramakrishnan, S. Vaithyanathan. (2006). “Managing information extraction: state of the art and research directions”. Proceedings of the ACM SIGMOD international conference on Management of data. pp. 799 – 800 | |
B. Berendt, A. Hotho, and G. Stumme. (2002). “Semantic Web Mining and the Representation, Analysis, and Evolution of Web Space”. Proceedings of the First International Semantic Web Conference on The Semantic Web. pp. 264 – 278 | |
B. Berendt, A. Hotho, G. Stumme. (2002). “Towards Semantic Web Mining”; ISWC '02: Proceedings of the First International Semantic Web Conference on The Semantic Web; Publisher: Springer-Verlag | |
C Mangold (2007). “A survey and classification of semantic search approaches”. International Journal of Metadata, Semantics and Ontologies, pp. 23–34. | |
D. Bitton, F. Faerber, L. Haas, J. Shanmugasundaram. (2006). “One platform for mining structured and unstructured data: dream or reality?”. Proceedings of the 32nd international conference on Very large data bases. pp. 1261 – 1262 | |
D. Buscaldi, P. Rosso, E. S. Arnal (2005). “A wordnet-based query expansion method for geo-graphical information retrieval”. Working Notes for the CLEF Workshop. | |
F. Figueira, J. Porto de Albuquerque, A. Resende, Geus, P. Lício de Geus, G. Olso (2009). “A visualization interface for interactive search refinement”. 3rd Annual Workshop on Human-Computer Interaction and IR, Washington DC. pp. 46-49. | |
G. Stummea, A. Hotho, B. Berendt. (2006). “Semantic Web Mining State of the art and future directions”. Journal of Web Semantic. Web Semantics: Science, Services and Agents on the World Wide Web 4. pp. 124–143. | |
H. Dong, FK Hussain, and E. Chang (2008). “A survey in semantic search technologies”. 2nd IEEE International Conference on Digital Ecosystems and Technologies. | |
J. Han, M. Kamber. (2001) “Data Mining Concepts and Techniques”. Academic Press, Morgan Kaufmarm Publishers. ISBN 1-55860-489-8. | |
K. Chang, B. He, Z. Zhang (2004, December). “Mining semantics for large scale integration on the web: evidences, insights, and challenges”. ACM SIGKDD Explorations Newsletter, Volume 6 , Issue 2. pp. 67-74. | |
L. Dey , S. K. M. Haque. (2009, July). “Studying the effects of noisy text on text mining applications”. Proceedings of The Third Workshop on Analytics for Noisy Unstructured Text Data. Barcelona, Spain | |
M. Hildebrand, J. Ossenbruggen, and L. Van Hardman (2007). “An analysis of search-based user interaction on the semantic web”. Report, CWI, Amsterdam, Holland. | |
M. Niepert, C. Buckner, J. Murdock, C. Allen. (2008). “InPhO: a system for collaboratively populating and extending a dynamic ontology”. Proceedings of the 8th ACM/IEEE-CS joint conference on Digital libraries, Pittsburgh PA, PA, USA. pp. 429-429 | |
M. Rajman, R. Besancon. (1997). “Text Mining - Knowledge extraction from unstructured textual data”. In Proceedings of the 7th IFIP Working Conference on Database Semantics (DS-7). pp. 7-10 | |
Miller, Guha, R., McCool, R. (2003). “E. Semantic Search”. Proceedings of the WWW’03, Budapest. | |
R. Ghani and Carlos. (2006, December). “Data mining for business applications”. KDD-2006 workshop. Volume 8, Issue 2. pp. 79 – 81 | |
R. J. Mooney, R. Bunescu. (2005). “Mining knowledge from text using information extraction”; ACM SIGKDD Explorations Newsletter. pp. 3 – 10 | |
Resource Description Framework (RDF) Schema Specification. (2000) In W3C Recommendation. | |
Tim Berners-Lee. “Semantic Web Roadmap”. http://www.W3.org/ | |
W. Fan, L. Wallace, S. Rich, Z. Zhang. (2006, September). “Tapping the power of text mining”. Communications of the ACM. Volume 49, Issue 9. pp. 76 – 82 | |
Web Ontology Language (OWL), http://www.w3.org/2004/OWL/. | |
Mr. Manoj Manuja
Infosys Technologies Ltd - India
manoj_manuja@infosys.com
Dr. Deepak Garg
- India
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