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Nirmala, K.
- Modern Thamizh Sandhi Rules Generator in NLP
Abstract Views :234 |
PDF Views:2
Authors
K. Nirmala
1,
M. K. Kalpana
1
Affiliations
1 Department of Computer Science, Quaid-E-Millath Goverment College for Women, IN
1 Department of Computer Science, Quaid-E-Millath Goverment College for Women, IN
Source
ICTACT Journal on Soft Computing, Vol 6, No 1 (2015), Pagination: 1110-1112Abstract
Thamizh sandhi rules generator deals with addition, deletion, getting changes with existing Information and this adjoining letters/sandhi grammar rules processing with indirect/bi-lingual machine translation. This Modern Thamizh Sandhi Rules Generator is implemented under Unicode based Indic Script. Modern Thamizh sandhi generation is the initial stage of developing the Word Formation rules in Thamizh computational method.Keywords
Thamizh Unicode, Diacritical Markings, Bilingual Machine Translation, Sandhi Rules, Computational Generator.References
- K. Rajan, V. Ramalingam and M. Ganesan, “Machine Learning for Sandhi Rules in Tamil”, Proceedings of the 11th International Conference INFITT, pp. 141-146, 2012.
- Manji Bhadra, Surjit Kumar Singh, Sachin Kumar, Subash, Muktanand Agrawal, R. Chandrasekhar, Sudhir K. Mishra, Girish Nath Jha, “Sanskrit Analysis System (SAS)”, Sanskrit Computational Linguistics, Vol. 5406, pp 116-133, 2009.
- Pawan Goyal, Vipul Arora and Laxmidhar Behara, “Analysis of Sanskrit Text: Parsing and Semantic Relations”, Sanskrit Computational Linguistics, pp. 200-218, 2009.
- Priyanka Gupta1 and Vishal Goyal, “Implementation of Rule Based Algorithm for Sandhi - Vicheda of Compound Hindi Words”, International Journal of Computer Science Issues, Vol. 3, pp. 45-49, 2009.
- Chimsuk Tawee and Surapong Auwatanamongkol, “An Incremental framework for a Thai-English Machine Translation System using a LFG tree structure as an Interlingual”, International Journal of Computer Science and Engineering, Vol. 2, No. 2, pp. 280-288, 2010.
- Judith Francisca Islam, Mohammad Mamun Mia and Dr. S. M. Monzurur Rahman, “Adapting rule based machine translation from English to Bangla”, Indian Journal of Computer Science and Engineering, Vol. 2, No. 3, pp. 334-342, 2011.
- S. Saraswathi, P. Kanivadhana, M. Anusiya and S. Sathiya, “Bilingual Translation System”, International Journal of Computer Science and Engineering, Vol. 3 No. 3, 2011.
- B. Krithika, V. Ramalingam and K. Rajan, “Performance of machine learning methods for classification tasks”, International Journal of Computer Science and Engineering, Vol. 5, No. 6, 2013.
- T. Kameswara Rao and T. V.Prasad, “Key Issues in Vowel Based Splitting of Telugu Bigrams”, International Journal of Advanced Computer Science and Applications: Special Issue on Natural Language Processing, pp. 9-16, 2014.
- Omar Shirko, Nazlia Omar, Haslina Arshad and Mohammed Albared, “Machine Translation of Noun Phrases from Arabic to English Using Transfer-Based Approach”, Journal of Computer Science, Vol. 6, No. 3, pp. 350-356, 2010.
- Arabic-Malay Machine Translation Using Rule-Based Approach, available at http://ww.itimes.com/citizen-journalism/arabic-malay-machine-translation-using-rule-based-approach.
- U. S. Tiwary and Tanveer Siddiqui, “Natural Language Processing and Information Retrieval”, Oxford University Press India, 2008 .
- http://en.wikipedia.org/wiki/Tamil_scrip
- Semantic Queries in Distributed Relational Database Using Global Ontology Construction
Abstract Views :180 |
PDF Views:0
Authors
R. Megala
1,
K. Nirmala
1
Affiliations
1 Department of Computer Science, University of Madras, IN
1 Department of Computer Science, University of Madras, IN
Source
ICTACT Journal on Soft Computing, Vol 5, No 3 (2015), Pagination: 942-945Abstract
Semantic web refers to the extension of the World Wide Web and it will provide a common framework which makes data available for reusing and sharing. Ontology is the backbone of Semantic web which is used to access relational database in Semantic web. This paper proposes a new approach which enables Semantic web application to access distributed relational databases. The method involves two main phases. In the first phase, have focus to construct one or more local ontologies. In the second phase, have focus to construct a global ontology to access distributed relational databases. Global ontology was constructed by merging one or more local ontologies. Global ontology supports a high level view of the database. This approach uses protege 4.3 tools for constructing ontologies.Keywords
Semantic Web, Local Ontology, Global Ontology, Protege Tool, Distributed Relational Database.- Searching and Tracking of Location by Proxy Based Approach
Abstract Views :164 |
PDF Views:3
Authors
K. Nirmala
1,
B. Kanimozhi
1
Affiliations
1 Department of Computer Science, Quaid-E-Millath Government College for women, IN
1 Department of Computer Science, Quaid-E-Millath Government College for women, IN
Source
ICTACT Journal on Soft Computing, Vol 7, No 2 (2017), Pagination: 1386-1389Abstract
Location based services became an important application in recent world. Users can search a location using smart phones and can also track the location. It is also possible for the users to retrieve information about the nearest location. The objective of this paper is to reduce the respond time of the server for the user queries. A proxy based approach is proposed to reduce the waiting time of the user and to increase the information about the location. Many location based services, provides details about the user queries. The proxy based approach creates an Estimated Valid Region which reduces the number of queries approaching the server there by reducing the waiting time of the mobile clients due to server load.Keywords
Nearest Neighbour Query, Window Query, Spatial Query Processing, Location-Based Service, Mobile Computing.References
- Jiun-Long Huang and Chen-Che Huang, “A Proxy-Based Approach to Continuous Location-based Spatial Queries in Mobile Environments”, IEEE Transactions on Knowledge and Data Engineering, Vol. 25, No. 2, pp. 260-273, 2013.
- Dik Lun Lee, Jianliang Xu, Baihua Zheng and Wang-Chien Lee, “Data Management in Location- Dependent Information Services”, IEEE Pervasive Computing, Vol. 1, No. 3, pp. 65-72, 2002.
- B. Zheng, J. Xu and D.L. Lee, “Cache Invalidation and Replacement Strategies for Location-Dependent Data in Mobile Environments”, IEEE Transactions on Computers, Vol. 15, No. 10, pp. 1141-1153, 2002.
- B. Zheng and D.L. Lee, “Processing Location-Dependent Queries in a Multi-Cell Wireless Environment”, Proceedings of 2nd ACM International Workshop on Data Engineering for Wireless and Mobile Access, pp. 54-65, 2001.
- X. Gao and A.R. Hurson, “Location Dependent Query Proxy”, Proceedings of ACM Symposium on Applied Computing, pp. 1120-1124, 2005.
- X. Gao, J. Sustersic and A.R. Hurson, “Window Query Processing with Proxy Cache”, Proceedings of 7th IEEE International Conference on Mobile Data Management, pp. 1-8, 2006.
- Location Based Services, Available at: https://en.wikipedia.org/wiki/Location-based_service
- Proxy Server, Available at: http://www.tutorialspoint.com/internet_technologies/proxy_servers.htm
- Reliable Cognitive Dimensional Document Ranking by Weighted Standard Cauchy Distribution
Abstract Views :181 |
PDF Views:3
Authors
Affiliations
1 Deparment of Computer Science, Manonmaniam Sundaranar University, IN
2 Department of Computer Science, Quaid-e-Millath Government College for Women, IN
1 Deparment of Computer Science, Manonmaniam Sundaranar University, IN
2 Department of Computer Science, Quaid-e-Millath Government College for Women, IN
Source
ICTACT Journal on Soft Computing, Vol 7, No 3 (2017), Pagination: 1437-1442Abstract
Categorization of cognitively uniform and consistent documents such as University question papers are in demand by e-learners. Literature indicates that Standard Cauchy distribution and the derived values are extensively used for checking uniformity and consistency of documents. The paper attempts to apply this technique for categorizing question papers according to four selective cognitive dimensions. For this purpose cognitive dimensional keyword sets of these four categories (also termed as portrayal concepts) are assumed and an automatic procedure is developed to quantify these dimensions in question papers. The categorization is relatively accurate when checked with manual methods. Hence simple and well established term frequency / inverse document frequency 'tf/ IDF' technique is considered for automating the categorization process. After the documents categorization, standard Cauchy formula is applied to rank order the documents that have the least differences among Cauchy value, (according to Cauchy theorem) so as obtain consistent and uniform documents in an order or ranked. For the purpose of experiments and social survey, seven question papers (documents) have been designed with various consistencies. To validate this proposed technique social survey is administered on selective samples of e-learners of Tamil Nadu, India. Results are encouraging and conclusions drawn out of the experiments will be useful to researchers of concept mining and categorizing documents according to concepts. Findings have also contributed utility value to e-learning system designers.Keywords
Standard Cauchy Distribution, Document Categorization, Concept Extraction, Cognitive Dimensions, Term Frequencies.References
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- M. Jelasity, Alberto Montresor and Ozalp Babaoglu, “Gossip-based Aggregation in Large Dynamic Networks”, ACM Transactions on Computer Systems, Vol. 23, No. 3, pp. 219-252, 2005.
- S. Rajarajeswari, “A Novel Exhaustive Criterion Based Load Balancing Algorithm for e-Learning Platform by Data Grid Technologies”, International Journal of Advanced Networking and Applications, Vol. 4, No. 6, pp. 1786-1792, 2013.
- S. Florence Vijila and K. Nirmala, “Quantification of Portrayal Concepts using tf-IDF Weighting”, International Journal of Information Sciences and Techniques, Vol. 3, No. 5, pp. 1-6, 2013.
- S. Florence Vijila and K. Nirmala, “Structural Effectiveness for Concept Extraction through Conditional Probability”, Advances in Natural and Applied Sciences, Vol. 9, No. 7, pp. 39-47, 2015.
- Oren Zamir and Oren Etzioni, “Web Document Clustering: A Feasibility Demonstration”, Proceedings of the 21st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 46-54, 1998.
- T.C. Tseng, H.C. Chu, G.J. Hwang and C.C. Tsai, “Development of an Adaptive Learning System with Two Sources of Personalization Information”, International Journal of Computers and Education, Vol. 51, No. 2, pp. 776-789, 2008.
- Masaru Ohba and Katsuhiko Gondow, “Toward Mining ‘Concept Keywords’ from Identifiers in Large Software Projects”, Proceedings of International Workshop on Mining Software Repositories, pp. 1-5, 2005.
- Ming-Hsiung Ying and Heng-Li Yang, “Computer Aided Generation of Item Banks based on Ontology and Bloom’s Taxonomy”, Proceedings of International Conference on Web-Based Learning, pp. 157-166, 2008.
- Robert M Gagne, “The Conditions of Learning and Theory of Instructions”, 4th Edition, Wadsworth Publishing Co Inc, 1985.
- M. Suriakala and T.G. Sambanthan, “Problem Centric Objectives for Conflicting Technical Courses”, The Indian Journal of Technical Education, Vol. 31, No. 2, pp. 87-90, 2008.
- S.M. Kamruzzaman, Farhana Haider and Ahmed Ryadh Hasan, “Text Classification using Association Rule with a Hybrid Concept of Naive Bayes Classifier and Genetic Algorithm”, Proceedings of 7th International Conference on Computer and Information Technology, pp. 682-687, 2004.
- B.A.V. Sharma, “Research Methods in Social Sciences”, Sultan Chand and Sons Publications, 1988,
- S. 14, G. Manoharan and K. Nirmala, “Trust Worthiness on Load Balance in Grids using Standard Cauchy Distribution”, Research Journal of Applied Sciences, Engineering and Technology, Vol. 8, No. 16, pp. 1833-1837, 2014.