Faculty Publications
Permanent URI for this communityhttps://idr.nitk.ac.in/handle/123456789/18736
Publications by NITK Faculty
Browse
5 results
Search Results
Item Sentiment analysis based approaches for understanding user context in Web content(2013) Kamath S․, S.S.; Bagalkotkar, A.; Khandelwal, A.; Pandey, S.; Poornima, K.In our day to day lives, we highly value the opinions of friends in making decisions about issues like which brand to buy or which movie to watch. With the increasing popularity of blogs, online reviews and social networking sites, the current trend is to look up reviews, expert opinions and discussions on the Web, so that one can make an informed decision. Sentiment analysis, also known as opinion mining is the computational study of opinions, sentiments and emotions expressed in natural language for the purpose of decision making. Sentiment analysis applies natural language processing techniques and computational linguistics to extract information about sentiments expressed by authors and readers about a particular subject, thus helping users in making sense of huge volume of unstructured Web data. Applications like review classification, product review mining and trend prediction benefit from sentiment analysis based techniques. This paper presents a study of different approaches in this field, the state of the art techniques and current research in Sentiment Analysis based approaches for understanding user's context. © 2013 IEEE.Item A note on ambiguity of internal contextual grammars(2006) Kuppusamy, L.In this paper, we continue the study of ambiguity of internal contextual grammars which was investigated in Ilie [On ambiguity in internal contextual languages, in: C. Martin-Vide (Ed.), Second Int. Conf. on Mathematical Linguistics, Tarragona, 1996, John Benjamins, Amsterdam, 1997, pp. 29-45] and Martin-Vide et al. [Attempting to define the ambiguity in internal contextual languages, in: C. Martin-Vide (Ed.), Second Int. Conf. on Mathematical Linguistics, Tarragona, 1996, John Benjamins, Amsterdam, 1997, pp. 59-81]. We solve some open problems formulated in these papers. The main results are: (i) there are inherently 1-ambiguous languages with respect to internal contextual grammars with arbitrary choice which are 0-unambiguous with respect to finite choice, (ii) there are inherently 2-ambiguous languages with respect to internal contextual grammars with arbitrary choice which are 1-unambiguous with respect to regular choice, and (iii) there are inherently 2-ambiguous languages with respect to depth-first internal contextual grammars with arbitrary choice which are 1-unambiguous with respect to finite choice. © 2006 Elsevier B.V. All rights reserved.Item Simplified and Improved Analytical Hierarchy Process Aid for Selecting Candidate Network in an Overlay Heterogeneous Networks(Kluwer Academic Publishers barbara.b.bertram@gsk.com, 2015) Chandavarkar, B.R.; Guddeti, G.R.M.Analytical hierarchy process (AHP) is one of the pairwise comparison, attributes weight calculation approach of multiple attribute decision making aid to select the candidate network for seamless handoff in an overlay heterogeneous network. The main challenging issue in AHP is manually computing the reciprocal matrix results in an inconsistency indicated by the consistency ratio >0.1. This paper proposes a simplified and improved AHP (SI-AHP), which accepts the perceived one-dimensional linguistic values of the attributes from the decision maker. Further, SI-AHP is used to automatically compute the reciprocal matrix for the attribute weights calculation with the minimum involvement of the decision maker resulting in reduced computational time and improved consistency. The consistency ratio of SI-AHP is further improved by deriving the reciprocal matrix of pairwise comparison of any one of the attribute to others. Using the MATLAB simulations, the proposed SI-AHP is evaluated for the consistency ratio of voice and download traffic and also for 78,125 different combinations of one-dimensional linguistic values of the attributes. SI-AHP’s weight calculated for the decision attributes is used in the multiple attribute decision making approach for selecting the candidate network in an overlay heterogeneous network. © 2015, Springer Science+Business Media New York.Item An overview of the shared task on machine translation in Indian languages (MTIL)-2017(De Gruyter peter.golla@degruyter.com, 2019) Anand Kumar, M.A.; Premjith, B.; Singh, S.; Rajendran, S.; Padannayil, K.P.In recent years, the multilingual content over the internet has grown exponentially together with the evolution of the internet. The usage of multilingual content is excluded from the regional language users because of the language barrier. So, machine translation between languages is the only possible solution to make these contents available for regional language users. Machine translation is the process of translating a text from one language to another. The machine translation system has been investigated well already in English and other European languages. However, it is still a nascent stage for Indian languages. This paper presents an overview of the Machine Translation in Indian Languages shared task conducted on September 7-8, 2017, at Amrita Vishwa Vidyapeetham, Coimbatore, India. This machine translation shared task in Indian languages is mainly focused on the development of English-Tamil, English-Hindi, English-Malayalam and English-Punjabi language pairs. This shared task aims at the following objectives: (a) to examine the state-of-the-art machine translation systems when translating from English to Indian languages; (b) to investigate the challenges faced in translating between English to Indian languages; (c) to create an open-source parallel corpus for Indian languages, which is lacking. Evaluating machine translation output is another challenging task especially for Indian languages. In this shared task, we have evaluated the participant's outputs with the help of human annotators. As far as we know, this is the first shared task which depends completely on the human evaluation. © 2019 Walter de Gruyter GmbH, Berlin/Boston.Item Transfer learning based code-mixed part-of-speech tagging using character level representations for Indian languages(Springer Science and Business Media Deutschland GmbH, 2023) Anand Kumar, A.K.; Padannayil, S.K.Massive amounts of unstructured content have been generated day-by-day on social media platforms like Facebook, Twitter and blogs. Analyzing and extracting useful information from this vast amount of text content is a challenging process. Social media have currently provided extensive opportunities for researchers and practitioners to do adequate research on this area. Most of the text content in social media tend to be either in English or code-mixed regional languages. In a multilingual country like India, code-mixing is the usual fashion witnessed in social media discussions. Multilingual users frequently use Roman script, an convenient mode of expression, instead of the regional language script for posting messages on social media and often mix it with English into their native languages. Stylistic and grammatical irregularities are significant challenges in processing the code-mixed text using conventional methods. This paper explains the new word embedding via character level representation as features for POS tagging the code-mixed text in Indian languages using the ICON-2015, ICON-2016 NLP tools contest data set. The proposed word embedding features are context-appended, and the well-known Support Vector Machine (SVM) classifier has been used to train the system. We have combined the Facebook, Twitter, and WhatsApp code-mixed data of three Indian languages to train the Transfer learning based language-independent and source independent POS tagging. The experimental results demonstrated that the proposed transfer method achieved state-of-the-art accuracy in 12 systems out of 18 systems for the ICON data set. © 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.