Tvgeetha

Scopus Publications

Genetically and semantically aware homogeneous network for prediction and scoring of comorbidities
Karpaga Priyaa Kartheeswaran, Arockia Xavier Annie Rayan, Geetha Thekkumpurath Varrieth
Computers in Biology and Medicine, 2024
OBJECTIVE: Patients with comorbidities are highly prone to mortality risk than those suffering from a single disease. Therefore, quantification and prediction of disease comorbidities is necessary to stratify the mortality risk of the patients, predict the probability of their occurrence, design treatment strategies, and to prevent the progression of diseases. Enriching comorbidity disease relationships with rich semantics established by genetic components play a vital role in effectively quantifying and predicting comorbidities. However, the existing studies have not extensively explored the semantic richness conveyed by different types of genetic links connecting the comorbidity pairs. METHODS: To solve this, a novel genetic-semantic aware weighted homogeneous network-based method, GSWHomoNet is proposed which first constructs the gene enriched comorbidity heterogeneous network, CoGHetNet with encoded genetic semantic aware weighted meta-path instance disease pair embedding to obtain an enhanced disease node embedding of the network. For enhanced comorbidity prediction and scoring, both direct and indirect semantically enriched comorbidity relationships of the disease nodes is preserved while transforming heterogeneous to homogeneous comorbidity network GSWHomoNet. The proposed GSWHomoNet not only helps discover comorbidity links transductively between known-known disease pairs but also improves the inductive link prediction between known-unknown disease pairs by supplying unknown disease nodes with semantically enriched heterogeneous structural knowledge. RESULTS: The effectiveness of the proposed components is proved by AUC scores of 0.895 and 0.860, as well as AUPR scores of 0.903 and 0.873 for transductive and inductive link prediction respectively. In comorbidity scoring, GSWHomoNet outperformed other methods with a correlation result of 0.848. The effect of the improved association prediction ability of the genetic semantic aware weighted meta-path instance embedding based node embedding is proved on disease-microbe and bibliographic heterogeneous network datasets. For biological significance of GSWHomoNet-based comorbidity scoring, we compared it with gene, pathway, and protein-protein interaction (PPI) perspectives, revealing a stronger correlation with the PPI aspect. We identified a substantial number of predicted comorbidity disease pairs, with 77,456 and 48,972 pairs supported by literature evidence for transductive and inductive predictions, respectively. Additionally, we highlighted shared pathways and PPIs for these pairs, demonstrating the robustness of comorbidity predictions.
Retraction Note: Knowledge-enhanced temporal word embedding for diachronic semantic change estimation (Soft Computing, (2020), 24, 17, (12901-12918), 10.1007/s00500-020-04714-0)
J. Vijayarani, T. V. Geetha
Soft Computing, 2024
DRADTiP: Drug repurposing for aging disease through drug-target interaction prediction
Saranya Muniyappan, Arockia Xavier Annie Rayan, Geetha Thekkumpurath Varrieth
Computers in Biology and Medicine, 2024
Learning Joint Topic Representation for Detecting Drift in Social Media Text
J. Vijayarani, T.V. Geetha
International Journal of Uncertainty Fuzziness and Knowledge Based Systems, 2024
Social media texts like tweets and blogs are collaboratively created by human interaction. Rapidly changing trends are leading to topic drift in the social media text. This drift is usually associated with words and hashtags. However, geotags play an essential part in determining topic distribution with location context. The rate of change in the distribution of words, hashtags and geotags cannot be considered uniform and must be handled accordingly. This paper builds a topic model that associates the topic with a mixture of distributions of words, hashtags and geotags. Stochastic gradient Langevin dynamic model with varying mini-batch sizes is used to capture the changes due to the asynchronous distribution of words and tags. Topic representations with co-occurrence and location contexts are specified as hashtag context vector and geotag context vector respectively. These two vectors are jointly learned to yield topical word embedding vectors over time conditioned on hashtags and geotags that can predict location-based topical variations effectively. When evaluated with Chennai and UK geolocated Twitter data, the proposed joint topical word embedding model enhanced by the social tags context, outperforms other methods.
EGeRepDR: An enhanced genetic-based representation learning for drug repurposing using multiple biomedical sources
Saranya Muniyappan, Arockia Xavier Annie Rayan, Geetha Thekkumpurath Varrieth
Journal of Biomedical Informatics, 2023
Poetic and Semantic Features for Lyricist Identification from Tamil Film Lyrics
Karthika Ranganathan, T. V. Geetha
SN Computer Science, 2023
DTiGNN: Learning drug-target embedding from a heterogeneous biological network based on a two-level attention-based graph neural network
Saranya Muniyappan, Arockia Xavier Annie Rayan, Geetha Thekkumpurath Varrieth
Mathematical Biosciences and Engineering, 2023
<abstract> <p>Motivation: In vitro experiment-based drug-target interaction (DTI) exploration demands more human, financial and data resources. In silico approaches have been recommended for predicting DTIs to reduce time and cost. During the drug development process, one can analyze the therapeutic effect of the drug for a particular disease by identifying how the drug binds to the target for treating that disease. Hence, DTI plays a major role in drug discovery. Many computational methods have been developed for DTI prediction. However, the existing methods have limitations in terms of capturing the interactions via multiple semantics between drug and target nodes in a heterogeneous biological network (HBN). Methods: In this paper, we propose a DTiGNN framework for identifying unknown drug-target pairs. The DTiGNN first calculates the similarity between the drug and target from multiple perspectives. Then, the features of drugs and targets from each perspective are learned separately by using a novel method termed an information entropy-based random walk. Next, all of the learned features from different perspectives are integrated into a single drug and target similarity network by using a multi-view convolutional neural network. Using the integrated similarity networks, drug interactions, drug-disease associations, protein interactions and protein-disease association, the HBN is constructed. Next, a novel embedding algorithm called a meta-graph guided graph neural network is used to learn the embedding of drugs and targets. Then, a convolutional neural network is employed to infer new DTIs after balancing the sample using oversampling techniques. Results: The DTiGNN is applied to various datasets, and the result shows better performance in terms of the area under receiver operating characteristic curve (AUC) and area under precision-recall curve (AUPR), with scores of 0.98 and 0.99, respectively. There are 23,739 newly predicted DTI pairs in total.</p> </abstract>
Enhanced disease-disease association with information enriched disease representation
Karpaga Priyaa Kartheeswaran, Arockia Xavier Annie Rayan, Geetha Thekkumpurath Varrieth
Mathematical Biosciences and Engineering, 2023
<abstract> <p>Objective: Quantification of disease-disease association (DDA) enables the understanding of disease relationships for discovering disease progression and finding comorbidity. For effective DDA strength calculation, there is a need to address the main challenge of integration of various biomedical aspects of DDA is to obtain an information rich disease representation. Materials and Methods: An enhanced and integrated DDA framework is developed that integrates enriched literature-based with concept-based DDA representation. The literature component of the proposed framework uses PubMed abstracts and consists of improved neural network model that classifies DDAs for an enhanced literaturebased DDA representation. Similarly, an ontology-based joint multi-source association embedding model is proposed in the ontology component using Disease Ontology (DO), UMLS, claims insurance, clinical notes etc. Results and Discussion: The obtained information rich disease representation is evaluated on different aspects of DDA datasets such as Gene, Variant, Gene Ontology (GO) and a human rated benchmark dataset. The DDA scores calculated using the proposed method achieved a high correlation mainly in gene-based dataset. The quantified scores also shown better correlation of 0.821, when evaluated on human rated 213 disease pairs. In addition, the generated disease representation is proved to have substantial effect on correlation of DDA scores for different categories of disease pairs. Conclusion: The enhanced context and semantic DDA framework provides an enriched disease representation, resulting in high correlated results with different DDA datasets. We have also presented the biological interpretation of disease pairs. The developed framework can also be used for deriving the strength of other biomedical associations.</p> </abstract>
Building and Analysis of Tamil Lyric Corpus with Semantic Representation
Amta 2022 15th Conference of the Association for Machine Translation in the Americas Proceedings Workshop on Empirical Translation Process Research, 2022
Machine Learning: Concepts, Techniques and Applications
T V Geetha, S Sendhilkumar
Machine Learning Concepts Techniques and Applications, 2022
Machine Learning: Concepts, Techniques and Applications starts at basic conceptual level of explaining machine learning and goes on to explain the basis of machine learning algorithms. The mathematical foundations required are outlined along with their associations to machine learning. The book then goes on to describe important machine learning algorithms along with appropriate use cases. This approach enables the readers to explore the applicability of each algorithm by understanding the differences between them. A comprehensive account of various aspects of ethical machine learning has been discussed. An outline of deep learning models is also included. The use cases, self-assessments, exercises, activities, numerical problems, and projects associated with each chapter aims to concretize the understanding. Features Concepts of Machine learning from basics to algorithms to implementation Comparison of Different Machine Learning Algorithms – When to use them & Why – for Application developers and Researchers Machine Learning from an Application Perspective – General & Machine learning for Healthcare, Education, Business, Engineering Applications Ethics of machine learning including Bias, Fairness, Trust, Responsibility Basics of Deep learning, important deep learning models and applications Plenty of objective questions, Use Cases, Activity and Project based Learning Exercises The book aims to make the thinking of applications and problems in terms of machine learning possible for graduate students, researchers and professionals so that they can formulate the problems, prepare data, decide features, select appropriate machine learning algorithms and do appropriate performance evaluation.
Joint learning of author and citation contexts for computing drift in scholarly documents
J. Vijayarani, T. V. Geetha
International Journal of Machine Learning and Cybernetics, 2021
Pattern-based bootstrapping framework for biomedical relation extraction
S.S. Deepika, T.V. Geetha
Engineering Applications of Artificial Intelligence, 2021
Concept map information content enhancement using joint word embedding and latent document structure
Kodaikkaavirinaadan Urkalan, Geetha T. V.
International Journal on Semantic Web and Information Systems, 2020
Knowledge-enhanced temporal word embedding for diachronic semantic change estimation
J. Vijayarani, T. V. Geetha
Soft Computing, 2020
A neural network framework for predicting dynamic variations in heterogeneous social networks
Mathiarasi Balakrishnan, Geetha T. V.
Plos One, 2020
Phrase Extraction Using Pattern-Based Bootstrapping Approach
R. Hema, T. V. Geetha
Lecture Notes in Networks and Systems, 2020
Influential Researcher Identification in Academic Network Using Rough Set Based Selection of Time- Weighted Academic and Social Network Features
Manju G., Kavitha V., Geetha T.V.
Cognitive Analytics Concepts Methodologies Tools and Applications, 2020
Entity Resolution and Blocking: A Review
K.A. Vidhya, T.V. Geetha
Proceedings of the 2019 IEEE 9th International Conference on Advanced Computing Iacc 2019, 2019
Advances in neuroevolution through augmenting topologies - A case study
Mohamed Yilmaz Ibrahim, Rangarajan Sridhar, T.V. Geetha, S.S. Deepika
Proceedings of the 11th International Conference on Advanced Computing Icoac 2019, 2019
New crossover operators using dominance and co-dominance principles for faster convergence of genetic algorithms
G. Pavai, T. V. Geetha
Soft Computing, 2019
A new dynamic neighbourhood- based semantic dissimilarity measure for ontology
Sathiya Balasubramanian, Geetha T. V.
International Journal of Intelligent Information Technologies, 2019
A review on semantic similarity measures for ontology
B. Sathiya, T.V. Geetha
Journal of Intelligent and Fuzzy Systems, 2019
Bootstrapping of semantic relation extraction for a morphologically rich language: Semi-supervised learning of semantic relations
Balaji Jagan, Ranjani Parthasarathi, T V Geetha
International Journal on Semantic Web and Information Systems, 2019
Cross-Corpus Training with CNN to Classify Imbalanced Biomedical Relation Data
S. S. Deepika, M. Saranya, T. V. Geetha
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2019
A meta-learning framework using representation learning to predict drug-drug interaction
S.S. Deepika, T.V. Geetha
Journal of Biomedical Informatics, 2018
Automatic ontology learning from multiple knowledge sources of text
B Sathiya, T.V. Geetha
International Journal of Intelligent Information Technologies, 2018
Entity resolution framework using rough set blocking for heterogeneous web of data
K.A. Vidhya, T.V. Geetha
Journal of Intelligent and Fuzzy Systems, 2018
Multi-perspective and Domain Specific Tagging of Chemical Documents
S. S. Deepika, T. V. Geetha, Rajeswari Sridhar
Communications in Computer and Information Science, 2018
A supervised learning to rank approach for dependency based concept extraction and repository based boosting for domain text indexing
U. K. Naadan, T. V. Geetha, U. Kanimozhi, D. Manjula, R. Viswapriya, C. Karthik
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2018
A survey on crossover operators
G. Pavai, T. V. Geetha
ACM Computing Surveys, 2017
Resolving Entity on A Large scale: DEtermining Linked Entities and Grouping similar Attributes represented in assorted TErminologies
K. A. Vidhya, T. V. Geetha
Distributed and Parallel Databases, 2017
A metric based automatic selection of ontology matchers using bootstrapped patterns
Journal of Web Engineering, 2017
PSOM2—partitioning-based scalable ontology matching using MapReduce
B Sathiya, T V Geetha, K Saruladha
Sadhana Academy Proceedings in Engineering Sciences, 2017
Improving the freshness of the search engines by a probabilistic approach based incremental crawler
G. Pavai, T. V. Geetha
Information Systems Frontiers, 2017
Guest Editorial: Computational Intelligence and Applications
Vijayan Sugumaran, T. V. Geetha, D. Manjula, Hema Gopal
Information Systems Frontiers, 2017
Entity resolution for symptom vs disease for top-K treatments
K. A. Vidhya, R. Soorya, N. Saranavan, T. V. Geetha, M. Singaravelan
2017 4th International Conference on Advanced Computing and Communication Systems Icaccs 2017, 2017
Rough set theory for document clustering: A review
K.A. Vidhya, T.V. Geetha
Journal of Intelligent and Fuzzy Systems, 2017
Influential researcher identification in academic network using rough set based selection of time-weighted academic and social network features
Manju G., Kavitha V., Geetha T.V.
International Journal of Intelligent Information Technologies, 2017
Unsupervised domain ontology learning from text
Sree Harissh Venu, Vignesh Mohan, Kodaikkaavirinaadan Urkalan, Geetha T.V.
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2017
Recognition of chemical entities using pattern matching and functional group classification
R. Hema, T. V. Geetha
International Journal of Intelligent Information Technologies, 2016
Academic tweet classification with spreading activation based label propagation algorithm using tweet centric features
G. Manju, T. V. Geetha
ACM International Conference Proceeding Series, 2016
Mining chemical information in various forms: A review
R. Hema, T. V. Geetha
ACM International Conference Proceeding Series, 2016
Semantic querying based concept hierarchy construction for ontology learning
B. Sathiya, T. V. Geetha
ACM International Conference Proceeding Series, 2016
Dynamic learner profiling and automatic learner classification for adaptive e-learning environment
K.R. Premlatha, B. Dharani, T.V. Geetha
Interactive Learning Environments, 2016
Abstractive summarization: A hybrid approach for the compression of semantic graphs
J. Balaji, T.V. Geetha, Ranjani Parthasarathi
International Journal on Semantic Web and Information Systems, 2016
Academic tweet concept based co-author recommendation
Asian Journal of Information Technology, 2016
Unsupervised learning of semantic relations of a morphologically rich language
J. Balaji, P. Ranjani, T. V. Geetha
International Journal of Information and Communication Technology, 2016
Automatic generation of templates using ontology
S. Thenmalar, T. V. Geetha
ACM International Conference Proceeding Series, 2015
Modified PageRank for concept based search
Journal of Web Engineering, 2015
Patent search and trend analysis
A.M. Supraja, S. Archana, S. Suvetha, T.V. Geetha
Souvenir of the 2015 IEEE International Advance Computing Conference Iacc 2015, 2015
Learning content design and learner adaptation for adaptive e-learning environment: a survey
K. R. Premlatha, T. V. Geetha
Artificial Intelligence Review, 2015
Learning event patterns from news text using bootstrapping
E. Umamaheswari, T.V. Geetha
International Journal of Information and Communication Technology, 2015
Automatic construction of Tamil UNL dictionary
Ganesh J, Ranjani Parthasarathi, Geetha T. V
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2015
Automatic data extraction in deep web using bootstrapping approach
International Journal of Applied Engineering Research, 2015
Learning to rank experts using combination of multiple features of expertise
V. Kavitha, G. Manju, T.V. Geetha
Proceedings of the 2014 International Conference on Advances in Computing Communications and Informatics Icacci 2014, 2014
Enhanced ontology-based indexing and searching
S. Thenmalar, T.V. Geetha
Aslib Journal of Information Management, 2014
The modified concept based focused crawling using ontology
Journal of Web Engineering, 2014
Collaborative search using an implicitly formed academic network
Somu Renugadevi, T.V. Geetha, R.L. Gayathiri, S. Prathyusha, T. Kaviya
Aslib Journal of Information Management, 2014
Graph-based bootstrapping for coreference resolution
J. Balaji, T.V. Geetha, P. Ranjani
Journal of Intelligent Systems, 2014
Event mining through clustering
E. Umamaheswari, T.V. Geetha
Journal of Intelligent Systems, 2014
A graph based query focused multi-document summarization
J Balaji, T V Geetha, Ranjani Parthasarathi
International Journal of Intelligent Information Technologies, 2014
Pattern based bootstrapping technique for tamil POS tagging
Jayabal Ganesh, Ranjani Parthasarathi, T. V. Geetha, J. Balaji
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2014
Concept similarity based academic tweet community detection using label propagation
G. Manju, T. V. Geetha
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2013
Learning a concept based ranking model with user feedback
E. Umamaheswari, T. V. Geetha
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2013
A Tamil lyrics search and visualization system
Karthika Ranganathan, B. Barani, T. V. Geetha
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2013
Concept based personalized search and collaborative search using modified HITS algorithm
G. Pavai, E. Umamaheswari, T. V. Geetha
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2013
Raga identification of Carnatic music based on the construction of Raga model
Rajeswari Sridhar, T.V. Geetha
International Journal of Signal and Imaging Systems Engineering, 2013
Adaptive learning path generation using colored Petri nets based on behavioral aspects
B. Dharani, T. V. Geetha
2013 International Conference on Recent Trends in Information Technology Icrtit 2013, 2013
Modified Particle Swarm Optimization (MPSO) algorithm for Web Service Selection (WSS) problem
T. Geetha, M. Sathya
Proceedings 2012 International Conference on Data Science and Engineering Icdse 2012, 2012
An approach towards dynamic assembling of learning objects
K. Sathiyamurthy, T. V. Geetha, M. Senthilvelan
ACM International Conference Proceeding Series, 2012
A deconverter framework for Malayalam
Misiriya Shahul Hameed, C. N. Subalalitha, T. V. Geetha, Ranjani Parthasarathi
ACM International Conference Proceeding Series, 2012
Re-ranking of educational materials based on topic profile for E-learning
K.R. Premlatha, T.V. Geetha
International Conference on Recent Trends in Information Technology Icrtit 2012, 2012
Automatic organization and generation of presentation slides for e-learning
K. Sathiyamurthy, T. V. Geetha
International Journal of Distance Education Technologies, 2012
Automatic question generation from documents for E-learning
K. Sathiyamurthy, T.V. Geetha
International Journal of Metadata Semantics and Ontologies, 2012
Requirements Elicitation by Defect Elimination: An Indian Logic Perspective
Software and Intelligent Sciences New Transdisciplinary Findings, 2012
Clustering web services based on multi-criteria service dominance relationship using Peano Space filling curve
A Sarang Sukumar, Jayakumar Loganathan, T Geetha
Proceedings 2012 International Conference on Data Science and Engineering Icdse 2012, 2012
Prediction on proactive channel sensing strategy for cognitive radio
Jayakumar Loganathan, Sukumar A Sarang, T Geetha
Proceedings 2012 International Conference on Data Science and Engineering Icdse 2012, 2012
UNL based context clustering for news event detection
Proceedings of the 5th Indian International Conference on Artificial Intelligence Iicai 2011, 2011
Automatic extractive text summarization based on fuzzy logic: A sentence oriented approach
M. Esther Hannah, T. V. Geetha, Saswati Mukherjee
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2011
Adaptive personalization and Presentation of Recommendations to Learners (APPRL) using Latent Dirichlet Allocation
Proceedings of the 5th Indian International Conference on Artificial Intelligence Iicai 2011, 2011
Anaphora resolution in tamil using universal networking language
Proceedings of the 5th Indian International Conference on Artificial Intelligence Iicai 2011, 2011
Popular trend summarization system
Proceedings of the 5th Indian International Conference on Artificial Intelligence Iicai 2011, 2011
Latent dirichlet allocation model for Raga identification of carnatic music
Sridhar
Journal of Computer Science, 2011
A multilevel UNL concept based Searching and Ranking
Webist 2011 Proceedings of the 7th International Conference on Web Information Systems and Technologies, 2011
Ontology based semantic similarly ranking of documents
S. Thenmalar, T. V. Geetha, S. Renuga Devi
Proceedings of the International Conference on Advances in Computing and Artificial Intelligence Acai 2011, 2011
Association of domain concepts with educational objectives for E-learning
K. Sathiyamurthy, T. V. Geetha
Compute 2010 the 3rd Annual ACM Bangalore Conference, 2010
Multi-robot learning using non-deterministic argument games
G.S. Mahalakshmi, T.V. Geetha
International Journal of Autonomous and Adaptive Communications Systems, 2010
Challenges in personalization for general information search
Proceedings of the 4th Indian International Conference on Artificial Intelligence Iicai 2009, 2009
Semantic role based tamil sentence generator
S. Lakshmana Pandian, T.V. Geetha
2009 International Conference on Asian Language Processing Recent Advances in Asian Language Processing Ialp 2009, 2009
Reasoning and evolution of consistent ontologies using NORM
International Journal of Artificial Intelligence, 2009
Design of Teaching Learning System based on Indian logic
Proceedings of the Iadis International Conference E Learning 2009 Part of the Iadis Multi Conference on Computer Science and Information Systems Mccsis 2009, 2009
Music information retrieval of tamil film music using melody and similarity measures
Proceedings of the 4th Indian International Conference on Artificial Intelligence Iicai 2009, 2009
Document summarization and information extraction for generation of presentation slides
K. Gokul Prasad, H. Mathivanan, T.V Greetha, M. Jayaprakasam
Artcom 2009 International Conference on Advances in Recent Technologies in Communication and Computing, 2009
CRF models for tamil part of speech tagging and chunking
S. Lakshmana Pandian, T. V. Geetha
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2009
Automatic tamil content generation
S. Kohilavani, T. Mala, T.V. Geetha
2009 International Conference on Intelligent Agent and Multi Agent Systems Iama 2009, 2009
Argument-based learning communities
G.S. Mahalakshmi, T.V. Geetha
Knowledge Based Systems, 2009
Formal definitions of reason fallacies to aid defect exploration in argument gaming
G. S. Mahalakshmi, T. V. Geetha
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2009
Gautama - Ontology Editor Based on Nyaya Logic
G. S. Mahalakshmi, T. V. Geetha, Arun Kumar, Dinesh Kumar, S. Manikandan
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2009
An Indian logic-based argument representation formalism for knowledge-sharing
G.S. Mahalakshmi, T.V. Geetha
Logic Journal of the Igpl, 2009
Architecture for effective personalised web search
S. Sendhilkumar, T.V. Geetha
International Journal of Computer Applications in Technology, 2009
An Indian logic-based knowledge-sharing architecture for virtual knowledge communities
G.S. Mahalakshmi, M. Karpagaraj, T.V. Geetha
International Journal of Networking and Virtual Organisations, 2009
Music information retrieval of Carnatic songs based on carnatic music singer identification
Rajeswari Sridhar, T. V. Geetha
Proceedings of the 2008 International Conference on Computer and Electrical Engineering Iccee 2008, 2008
Personalized ontology for web search personalization
S. Sendhilkumar, T. V. Geetha
Compute 2008 the 1st ACM Bangalore Annual Conference, 2008
Result evaluation strategies for peer selection in P2P
M. Harish, N. Anandavelu, N. Anbalagan, G. S. Mahalakshmi, T. V. Geetha
Compute 2008 the 1st ACM Bangalore Annual Conference, 2008
Tamil question classification using morpheme features
S. Lakshmana Pandian, T. V. Geetha
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2008
The logic of reasoning by procedural argumentation for knowledge sharing
Proceedings International Conference on Computational Intelligence and Multimedia Applications Iccima 2007, 2008
Two level language models for improving the performance of Tamil speech recognition
Proceedings International Conference on Computational Intelligence and Multimedia Applications Iccima 2007, 2008
Visualization of plagiarism detected in documents
Proceedings International Conference on Computational Intelligence and Multimedia Applications Iccima 2007, 2008
Game theoretic model for P2P trust management
D.S. Guru, M.G. Suraj
Proceedings International Conference on Computational Intelligence and Multimedia Applications Iccima 2007, 2008
Tamil document summarization using semantic graph method
Proceedings International Conference on Computational Intelligence and Multimedia Applications Iccima 2007, 2008
Personalized web search using enhanced probabilistic user conceptual index
Journal of Intelligent Systems, 2008
Semantic information extraction from Tamil documents
S. Lakshmana Pandian, J. Devakumar, T.V. Geetha
International Journal of Metadata Semantics and Ontologies, 2008
GVP model based temporal visualisation of user-centric data
T. Mala, P. Bhargavi, T.V. Geetha
International Journal of Metadata Semantics and Ontologies, 2008
Visualizing author attribution using Blobby objects
T. Mala, T.V. Geetha
Computer Graphics Imaging and Visualisation New Advances CGIV 2007, 2007
An evaluation of personalized web search for an individual user
International Conference on Artificial Intelligence and Pattern Recognition 2007 Aipr 2007, 2007
I-KARe - A rational approach to knowledge acquisition and reasoning using Indian logic based knowledge models
Proceedings of the 3rd Indian International Conference on Artificial Intelligence Iicai 2007, 2007
Personalized web search using a modified User Conceptual Index based on a Search Flow Graph
Proceedings of the 3rd Indian International Conference on Artificial Intelligence Iicai 2007, 2007
Named entity recognition in Tamil using context-cues and the E-M algorithm
Proceedings of the 3rd Indian International Conference on Artificial Intelligence Iicai 2007, 2007
Comparison of performance of enhanced morpheme-based language model with different word-based language models for improving the performance of Tamil speech recognition system
S. Saraswathi, T. V. Geetha
ACM Transactions on Asian Language Information Processing, 2007
Language models for Tamil speech recognition system
IETE Technical Review Institution of Electronics and Telecommunication Engineers India, 2007
Improvement in performance of tamil phoneme recognition using variable length and hybrid language models
S. Saraswathi, T.V. Geetha
Proceedings of Icscn 2007 International Conference on Signal Processing Communications and Networking, 2007
A model for the world knowledge representation based on nyaya theory
Journal of the Institution of Engineers India Part CP Computer Engineering Division, 2007
User's search behavior graph for aiding personalized Web search
S. Sendhilkumar, T. V. Geetha
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2007
Trusted domain web services for delivering e-government services
S. Swamynathan, A. Kannan, T. V. Geetha
Advances in Computer Science and Eng Reports and Monographs Innovative Applications of Information Technology for the Developing World Proc of the 3rd Asian Applied Comput Conf Aacc 2005, 2007
Design and analysis of a game theoretic model for P2P trust management
M. Harish, N. Anandavelu, N. Anbalagan, G. S. Mahalakshmi, T. V. Geetha
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2007
A mathematical model for argument procedures based on indian philosophy
Proceedings of the IASTED International Conference on Artificial Intelligence and Applications Aia 2006, 2006
Time scale modification and vocal tract length normalization for improving the performance of Tamil speech recognition system implemented using language independent segmentation algorithm
S. Saraswathi, T. V. Geetha
International Journal of Speech Technology, 2006
Composite event monitoring in XML repositories using generic rule framework for providing reactive e-services
S. Swamynathan, A. Kannan, T.V. Geetha
Decision Support Systems, 2006
Swara identification for South Indian Classical music
Rajeswari Sridhar, T.V. Geetha
Proceedings 9th International Conference on Information Technology Icit 2006, 2006
Topical and temporal visualization using wavelets
T. Mala, T. V. Geetha, Sathish Kumar
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2006
Relation-based information retrieval
D. Manjula, T. V. Geetha
Journal of Information and Knowledge Management, 2005
Web search using personalized user conceptual index
Proceedings of the 2nd Indian International Conference on Artificial Intelligence Iicai 2005, 2005
Mixed language speech recognition and automated dialog management
Proceedings of the 2nd Indian International Conference on Artificial Intelligence Iicai 2005, 2005
Visualization of biological patterns in event detection and tracking based on SRP algorithm
T. Mala, T.V. Geetha
Proceedings of the International Conference on Information Visualisation, 2005
Introducing pitch modification in residual excited LPC Based tamil text-to-speech synthesis
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2004
Semantic search engine
D. Manjula, T. V. Geetha
Journal of Information and Knowledge Management, 2004
Semantics based information retrieval using conceptual indexing of documents
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2004
Building language models for tamil speech recognition system
S. Saraswathi, T. V. Geetha
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2004
Implementation of tamil speech recognition system using neural networks
S. Saraswathi, T. V. Geetha
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2004
Description Logic based knowledge representation for information extraction and query processing
D Manjula, T V Geetha
IETE Journal of Research, 2004
Document knowledge representation using description logics for information extraction and querying
D. Manjula, G. Aghila, T.V. Geetha
Proceedings ITCC 2003 International Conference on Information Technology Computers and Communications, 2003
Automatic generation of description logic representation of documents
Proceedings of the International Conference on Artificial Intelligence IC AI 2003, 2003
Text mining in 'Request for Comments Document Series'
S. Gurusamy, D. Manjula, T.V. Geetha
Proceedings Language Engineering Conference Lec 2002, 2002
Generation of natural language text using perspective descriptor in frames
G V Uma, T V Geetha
IETE Journal of Research, 2001
An intelligent query language for temporal databases
A Kannan, T V Geetha, M Marikkannan
IETE Journal of Research, 2001
Natural language representatiom - A connectionist approach
T.V. Geetha, R.K. Subramanian
IEEE Region 10 Annual International Conference Proceedings TENCON, 1991
Representing Natural Language with Prolog
T.V. Geetha, R.K. Subramanian
IEEE Software, 1990
Extraction and representation of facts from legal briefs
M.G. Venkateshmurthy, T.V. Geetha, R.K. Subramanian
Journal of Intelligent and Robotic Systems, 1990
Natural language understanding - an effort to interpret pragmatics
T V Geetha, R K Subramanian
IETE Journal of Research, 1988

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Machine learning for Pre-clinical drug repurposing

Games for Lifestyle Change

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