Role of Natural Language Processing in Information Retrieval; Challenges and Opportunities
This paper aims to analyze the role of natural
language processing (NLP). The paper will discuss the role in the
context of automated data retrieval, automated question answer, and
text structuring. NLP techniques are gaining wider acceptance in real
life applications and industrial concerns. There are various
complexities involved in processing the text of natural language that
could satisfy the need of decision makers. This paper begins with the
description of the qualities of NLP practices. The paper then focuses
on the challenges in natural language processing. The paper also
discusses major techniques of NLP. The last section describes
opportunities and challenges for future research.
[1] Nadial M., Panggabean E., and S. Meryana, “A Study of Parsing Process on Natural Language Processing in Bahasa Indonesia,” Computational Science and Engineering, pp. 309-316, Dec. 2013.
[2] F. Davide., and C. Gerardo, “Empirical principles and an industrial case study in retrieving equivalent requirements via natural language processing techniques,” IEEE Transactions on Software Engineering, vol. 39, no. 1, pp. 18-44, Jan. 2013.
[3] D. Natalia, and S. David, “Application of Natural Language Processing and Evidential Analysis to Web-Based Intelligence Information Acquisition,” European Intelligence and Security Informatics Conference, pp. 268-273, Aug. 2012
[4] J. Shaidah, and A. M. Hejab, “Automated Translation Machines: Challenges and a Proposed Solution,” International Conference on Intelligent Systems, Modelling and Simulation, pp. 77-82, Jan. 2011.
[5] I. Mohd, and A. Rodina, “Class diagram extraction from textual requirements using Natural language processing (NLP) techniques,” International Conference on Computer Research and Development, pp. 200-204, May 2010.
[6] B. Fedor, S. Bahar, W. Rene, M. Marie-Jean, and K. Birgitta, “Natural Language Processing for Semantic Assistance in Web Portals,” IEEE Sixth International Conference on Semantic Computing, pp. 67-74, Sep. 2012.
[7] L. Wenbin. “Toward consistency checking of natural language temporal requirements,” IEEE/ACM International Conference on Automated Software Engineering, pp. 651-655, Nov. 2011.
[8] Chris Buckley, Amit Singhal, Mandar Mitra, Gerard Salton. 1995. ``New Retrieval Approches Using SMART: TREC 4’’. In Proceedings of TREC4.
[9] Strzalkowski, Tomek and Jose Perez-Carballo. 1994. “Recent Developments in Natural Language Text Retrieval.” Proceedings of the Second Text REtrieval Conference (TREC-2), NIST Special Publication 500-215, pp. 123-136.
[10] Strzalkowski, Tomek, Jose Perez-Carballo and Mihnea Marinescu. 1996. “Natural Language Information Retirieval: TREC-4 Report.” Proceedings of the Third Text REtrieval Conference (TREC-4), NIST Special Publication 500-2xx.
[11] Brenner, Everett. "Beyond Boolean--New Approaches to Information Retrieval." National Federation of Abstracting and Information Services, Philadelphia, 1996
[12] Hayes, Philip J. and Gail Koerner. "Intelligent Text Technologies and Their Successful Use by the Information Industry". Proceedings of the Fourteenth National Online Meeting, 1993 : pp. 189-196.
[13] Jacobs, Paul S., ed. Text-Based Intelligent Systems: Current Research and Practice in Information Extraction and Retrieval. Hillsdale, NJ: Lawrence Erlbaum Associates, 1992.
[14] Liddy, Elizabeth. "Enhanced Text Retrieval Using Natural Language Processing." ASIS Bulletin (April/May 1998). On the Web at http://www.asis.org/Bulletin/Apr-98/liddy.html.
[15] Spink, Amanda and Howard Greisdorf. "Partial Relevance Judgments and Changes in Users' Information Problems During Online Searching." National Online Meeting, 18th Proceedings (1997): pp. 323-334.
[16] Callan, J. P. and Croft, W. B. An evaluation of query processing strategies using the TIPSTER collection. In Proceedings of the Sixteenth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (June 27 - July 1, Pittsbrugh, PA). ACM/SIGIR, New York, 1993, pp. 347–355.
[17] Chinchor, N., Hirschman, L., and Lewis, D. D. Evaluating message understanding systems: An analysis of the Third Message Understanding Conference (MUC-3). Computational Linguistics19, 3 (1993), 409–449.
[18] Guthrie, Louise and Leistensnider, James, `A Simple Probabilistic Approach to Classification and Routing’, Proceedings of the TIPSTER Text Program Phase II Workshop, Sponsored by Defense Advanced Research Projects Agency, May 6-8, 1996.
[19] Strzalkowski, Tomek. 1995. “Natural Language Information Retrieval” Information Processing and Management, Vol. 31, No. 3, pp. 397-417. Pergamon/Elsevier
[20] Feldman, Susan E. "Searching Natural Language Search Systems" Searcher (October, 1994): pp. 34-39.
[21] Feldman, Susan E. "Testing Natural Language: Comparing DIALOG, TARGET, and DR-LINK." ONLINE 0, No. 6 (Nov. 1996) pp. 71-79.
[22] Harman, Donna K., ed. The First Text Retrieval Conference (TREC-1). Bethesda, MD: National Institute of Standards and Technology, March 1993. (Available from NTIS: PB93-191641).
[1] Nadial M., Panggabean E., and S. Meryana, “A Study of Parsing Process on Natural Language Processing in Bahasa Indonesia,” Computational Science and Engineering, pp. 309-316, Dec. 2013.
[2] F. Davide., and C. Gerardo, “Empirical principles and an industrial case study in retrieving equivalent requirements via natural language processing techniques,” IEEE Transactions on Software Engineering, vol. 39, no. 1, pp. 18-44, Jan. 2013.
[3] D. Natalia, and S. David, “Application of Natural Language Processing and Evidential Analysis to Web-Based Intelligence Information Acquisition,” European Intelligence and Security Informatics Conference, pp. 268-273, Aug. 2012
[4] J. Shaidah, and A. M. Hejab, “Automated Translation Machines: Challenges and a Proposed Solution,” International Conference on Intelligent Systems, Modelling and Simulation, pp. 77-82, Jan. 2011.
[5] I. Mohd, and A. Rodina, “Class diagram extraction from textual requirements using Natural language processing (NLP) techniques,” International Conference on Computer Research and Development, pp. 200-204, May 2010.
[6] B. Fedor, S. Bahar, W. Rene, M. Marie-Jean, and K. Birgitta, “Natural Language Processing for Semantic Assistance in Web Portals,” IEEE Sixth International Conference on Semantic Computing, pp. 67-74, Sep. 2012.
[7] L. Wenbin. “Toward consistency checking of natural language temporal requirements,” IEEE/ACM International Conference on Automated Software Engineering, pp. 651-655, Nov. 2011.
[8] Chris Buckley, Amit Singhal, Mandar Mitra, Gerard Salton. 1995. ``New Retrieval Approches Using SMART: TREC 4’’. In Proceedings of TREC4.
[9] Strzalkowski, Tomek and Jose Perez-Carballo. 1994. “Recent Developments in Natural Language Text Retrieval.” Proceedings of the Second Text REtrieval Conference (TREC-2), NIST Special Publication 500-215, pp. 123-136.
[10] Strzalkowski, Tomek, Jose Perez-Carballo and Mihnea Marinescu. 1996. “Natural Language Information Retirieval: TREC-4 Report.” Proceedings of the Third Text REtrieval Conference (TREC-4), NIST Special Publication 500-2xx.
[11] Brenner, Everett. "Beyond Boolean--New Approaches to Information Retrieval." National Federation of Abstracting and Information Services, Philadelphia, 1996
[12] Hayes, Philip J. and Gail Koerner. "Intelligent Text Technologies and Their Successful Use by the Information Industry". Proceedings of the Fourteenth National Online Meeting, 1993 : pp. 189-196.
[13] Jacobs, Paul S., ed. Text-Based Intelligent Systems: Current Research and Practice in Information Extraction and Retrieval. Hillsdale, NJ: Lawrence Erlbaum Associates, 1992.
[14] Liddy, Elizabeth. "Enhanced Text Retrieval Using Natural Language Processing." ASIS Bulletin (April/May 1998). On the Web at http://www.asis.org/Bulletin/Apr-98/liddy.html.
[15] Spink, Amanda and Howard Greisdorf. "Partial Relevance Judgments and Changes in Users' Information Problems During Online Searching." National Online Meeting, 18th Proceedings (1997): pp. 323-334.
[16] Callan, J. P. and Croft, W. B. An evaluation of query processing strategies using the TIPSTER collection. In Proceedings of the Sixteenth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (June 27 - July 1, Pittsbrugh, PA). ACM/SIGIR, New York, 1993, pp. 347–355.
[17] Chinchor, N., Hirschman, L., and Lewis, D. D. Evaluating message understanding systems: An analysis of the Third Message Understanding Conference (MUC-3). Computational Linguistics19, 3 (1993), 409–449.
[18] Guthrie, Louise and Leistensnider, James, `A Simple Probabilistic Approach to Classification and Routing’, Proceedings of the TIPSTER Text Program Phase II Workshop, Sponsored by Defense Advanced Research Projects Agency, May 6-8, 1996.
[19] Strzalkowski, Tomek. 1995. “Natural Language Information Retrieval” Information Processing and Management, Vol. 31, No. 3, pp. 397-417. Pergamon/Elsevier
[20] Feldman, Susan E. "Searching Natural Language Search Systems" Searcher (October, 1994): pp. 34-39.
[21] Feldman, Susan E. "Testing Natural Language: Comparing DIALOG, TARGET, and DR-LINK." ONLINE 0, No. 6 (Nov. 1996) pp. 71-79.
[22] Harman, Donna K., ed. The First Text Retrieval Conference (TREC-1). Bethesda, MD: National Institute of Standards and Technology, March 1993. (Available from NTIS: PB93-191641).
@article{"International Journal of Business, Human and Social Sciences:68656", author = "Khaled M. Alhawiti", title = "Role of Natural Language Processing in Information Retrieval; Challenges and Opportunities", abstract = "This paper aims to analyze the role of natural
language processing (NLP). The paper will discuss the role in the
context of automated data retrieval, automated question answer, and
text structuring. NLP techniques are gaining wider acceptance in real
life applications and industrial concerns. There are various
complexities involved in processing the text of natural language that
could satisfy the need of decision makers. This paper begins with the
description of the qualities of NLP practices. The paper then focuses
on the challenges in natural language processing. The paper also
discusses major techniques of NLP. The last section describes
opportunities and challenges for future research.
", keywords = "Data Retrieval, Information retrieval, Natural
Language Processing, Text Structuring.", volume = "8", number = "12", pages = "3940-5", }
