Varsha M. Pathak and Manish R. Joshi

Information Retrieval; SMS Based Information System; Vector Space Model; Minimum Edit Distance; Noisy Query; Transliterated Search

SMS based Information Systems is the need of the age. Most of the present SMS based information systems send one way SMS based informative text messages generated from respective knowledge systems. By applying information retrieval methodology using models like Vector Space Mode, the systems can allow its users to send queries as per their requirement of information. This makes the system more fruitful from the user’s point of view. This paper is about such initiatives for accessing relevant literature like poems, phrases, Rhymes, stories, abhang and much more. The mobile based quick library access system MQuickLib allows users to access such literature by formulating transliterated queries. The Vector Space Model is used to create the systems knowledge base by processing. The document terms and matched with the query terms by allowing variation in spelling due to transliteration style of the users. The matching score is assigned by devising a set of rules that identify the distance between two terms dk the term from document and qj the query term. The original Levenshtein’s minimum edit distance algorithm is modified by applying this rule based approach. These rules are identified by collecting SMS queries from users for a given set of known queries in Marathi (Devnagari). Experiments were carried out for the collection of Marathi and Hindi literature that mainly include songs, gazals, powadas, bharud and other types. These documents are available in a standard transliteration form like ITRANS (an Indic Transliteration System). This paper elaborated a rule based approach and analyses the results to select appropriate rule based model that is further applied for the development of MQuickLib system.

[1] Sanskrit documents collection : Home page, URL: http://www.sanskritdocuments.org,http://www.giitaayan.com/
[2] Rahis Shaikh Anwar Dilawar Shaikh, Rajiv Ratn Shah. SMS based FAQ retrieval for hindi, english and malayalam. 2013.
[3] CTIA annual wireless industry survey report. URL http://www.ctia.org/ industry-data/ctia-annual-wireless-industry-survey.
[4] Ian Ruthven and Mounia Lalmas. A survey on the use of relevance feedback for information access systems. The Knowledge Engineering Review, 18(02): 95–145, 2003.
[5] Pakray, Dr. Partha & Bhaskar, Pinaki. (2013). Transliterated Search System for Indian Languages.
[6] Sreangsu Acharyya, Sumit Negi, L Venkata Subramaniam, and Shourya Roy. Unsupervised learning of multilingual short message service (sms) dialect fromnoisy examples. In Proceedings of the second workshop on Analytics for noisy unstructured text data, pages 67–74. ACM, 2008.
[7] AiTi Aw, Min Zhang, Juan Xiao, and Jian Su. A phrase-based statistical model for sms text normalization. In Proceedings of the COLING/ACL on Main conference poster sessions, pages 33–40. Association for Computational Linguistics, 2006.
[8] Shahbaaz Mhaisale; Sangameshwar Patil; Kiran Mahamuni; Kiranjot Dhillon; Karan Parashar. Faq retrieval using noisy queries: English monolingual sub-task. In FIRE 2013 Shared Task on FAQ. DTU, Delhi, India, FIRE 2013, 2013.
[9] Govind Kothari, Sumit Negi, Tanveer A Faruquie, Venkatesan T Chakaravarthy, and L Venkata Subramaniam. SMS based interface for FAQ retrieval. In Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 2-Volume 2, pages 852–860. Association for Computational Linguistics, 2009.
[10] G Raghavendran. SMS based wireless home appliance control system. In Proceedingsof International Conference on Life Science and Technology (ICLST 2011), 2011.
[11] Pathak, V. M., Joshi, M. R. (2015). Natural Language Query Refinement Scheme for Indic Literature Information System on Mobiles. In Emerging ICT for Bridging the Future-Proceedings of the 49th Annual Convention of the Computer Society of India CSI Volume 2 (pp. 145-156). Springer, Cham.
[12] Majumder Prasenjit, Mitra Mandar, Agrawal Madhu, Mehta Parth (2015), Proceedings of the 7th Forum for Information Retrieval Evaluation. 10.1145/2838706.

Dr. Arun Behera

Phonetic; Sound; Spelling; Language; L2 Speaker; Pronunciation

English is one of only a handful few non phonetic dialects where there are heaps of oddities among spellings and sounds. Obviously, one of the fundamental reasons is that English has 26 letters that can generate 44 sounds. Letters of the English are stringed together in a specific order to shape words which are portrayed with phonetic features. There is an absence of pattern as far as letters and sounds are concerned thus making the pronunciation erratic especially for L2 speakers. It is therefore necessary that these errors are identified correctly for the non-native speakers of English to avoid lapses. This investigation attempts to distinguish and analyse the explanations behind this issue and also to offer a few recommendations to mitigate the issues relating to spelling and sound.

[1] Behera, Arun. (2012). Speaking English Fluently. New Delhi: Sanbun Publishers. [2] Behera, Arun. (2011). The World of Portmanteau Words. Chennai: Vijay Nicole Imprints Pvt Ltd. [3] Dhand, Deepika. (2018) Simplifying Spelling Structures. Mumbai: Himalaya Publishing House. Pp.v. [4] Howard, George Selby. (1741) The New Royal Cyclopaedia and Encyclopaedia. London: Alex Hogg. Pp 1078. [5] Jones, Daniel. 16th ed. (2003). Cambridge English Pronouncing Dictionary. Noida: Cambridge University Press. [6] Okeke, Nneka Umera. Spelling and Phonetic Inconsistencies in English: A Problem for Learners of English as a Foreign/Second Language. African Research Review Vol. 2 (1), Jan 2008. Pp 65-66. [7] Pink, Alderton M. & S. E. Thomas. (1994) English Grammar, Composition and Correspondence (12th ed.). Reading: Donnington Press. [8] Sharma, Tara Chand. (2003) Modern Methods of Teaching English. New Delhi: Sarup & Sons. Pp43.

ச.ராஜேஸ்வரி

வரலாற்று முக்கியத்துவம்; மதுரை; மன்னர்கள்

குழந்தை எழுத்தாளரான டாக்டர் பூவண்ணன் என்ற வே.தா.கோபாலகிருஷ்ணன் சிறுவர் உலகிற்காக நான்கு வரலாற்று நாவல்கள் இயற்றியுள்ளார். அதில் ஒன்று தான் ‘புலவர்மகன்’ என்ற நாவலாகும். மேலும் இவ்வரலாற்று நாவலுக்கு முன்பு பல சமூக நாவல்களை எழுதியுள்ளார். அவைகள் சிறுவர் உலகம் சார்ந்து இடம்பெற்றுள்ளதோடு சமூக மேம்பாட்டிற்கான படைப்புகளாக அமைந்துள்ளன. அந்தவகையில் புலவர்மகன் என்ற வரலாற்று நாவலின் மூலம் உணர்த்திய கருத்துகளைக் காணலாம்.

[1] ம.இராசசேகர தங்கமணி (ப.ஆ), பாண்டியர் வரலாறு (முதல் பாகம்), தமிழ்நாட்டுப் பாடநூல் நிறுவனம், 1978.
[2] டாக்டர் பூவண்ணன், டாக்டர் பூவண்ணனின் சிறுவர் இலக்கியக் களஞ்சியம் (தொகுதி – பதினொன்று), புலவர்மகன் (வரலாற்று நாவல்), பூவண்ணன் பதிப்பகம், கோவை, 2001.