Conference Papers
Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506
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Item Ontologies for specifying and reconciling contexts of web services(Elsevier, 2006) Sattanathan, S.; Narendra, N.C.; Maamar, Z.This paper presents an ontology-based approach for the specification (using OWL-C as a definition language) and reconciliation (using ConWeS as a mediation tool) of contexts of Web services. Web services are independent components that can be triggered and composed for the satisfaction of user needs (e.g., hotel booking). Because Web services originate from different providers, their composition faces the obstacle of the context heterogeneity featuring these Web services. An unawareness of this context heterogeneity during Web services composition and execution results in a lack of the quality and relevancy of information that permits tracking the composition, monitoring the execution, and handling exceptions. © 2006 Elsevier B.V. All rights reserved.Item NN based ontology mapping(Springer Verlag service@springer.de, 2013) Manjula Shenoy, K.; Shet, K.C.; Dinesh Acharya, U.The Semantic Web presents new opportunities for enabling modelling, sharing and reasoning with knowledge available on the web. These are made possible through the formal representation of the knowledge domain with ontologies. Ontology is also seen as a key factor for enabling interoperability across heterogeneous systems. Ontology mapping is required for combining distributed and heterogeneous ontologies. This paper introduces you to the problem of heterogeneity, and need for ontologies and mapping. Also gives an overview of some such ontology mapping systems together with a new system using neural network. The system designed takes OWL files as input and determines all kinds of matching such as 1:1,1:n,n:1,n:n between the entities. © 2013 Springer-Verlag.Item Ontology based approach for event detection in twitter datastreams(Institute of Electrical and Electronics Engineers Inc., 2015) Kaushik, R.; Apoorva Chandra, S.; Mallya, D.; Chaitanya, J.N.V.K.; Kamath S․, S.In this paper, we present a system that attempts to interpret relations in social media data based on automatically constructed dataset-specific ontology. Twitter data pertaining to the real world events such as the launch of products and the buzz generated by it, among the users of Twitter for developing a prototype of the system. Twitter data is filtered using certain tag-words which are used to build an ontology, based on extracted entities. Wikipedia data on the entities are collected and processed semantically to retrieve inherent relations and properties. The system uses these results to discover related entities and the relationships between them. We present the results of experiments to show how the system was able to effectively construct the ontology and discover inherent relationships between the entities belonging to two different datasets. © 2015 IEEE.Item Sociopedia: An interactive system for event detection and trend analysis for twitter data(Springer Science and Business Media Deutschland GmbH info@springer-sbm.com, 2016) Kaushik, R.; Apoorva Chandra, S.; Mallya, D.; Chaitanya, J.N.V.K.; Kamath S․, S.The emergence of social media has resulted in the generation of highly versatile and high volume data. Most web search engines return a set of links or web documents as a result of a query, without any interpretation of the results to identify relations in a social sense. In the work presented in this paper, we attempt to create a search engine for social media datastreams, that can interpret inherent relations within tweets, using an ontology built from the tweet dataset itself. The main aim is to analyze evolving social media trends and providing analytics regarding certain real world events, that being new product launches, in our case. Once the tweet dataset is pre-processed to extract relevant entities, Wiki data about these entities is also extracted. It is semantically parsed to retrieve relations between the entities and their properties. Further, we perform various experiments for event detection and trend analysis in terms of representative tweets, key entities and tweet volume, that also provide additional insight into the domain. © Springer India 2016.Item An Ontology Based Trust Framework for Sensor-Driven Pervasive Environment(Institute of Electrical and Electronics Engineers Inc., 2018) Karthik, N.; Ananthanarayana, V.S.Pervasive computing is an environment consisting set of sensor nodes with the characteristics of perception, computation and communication capabilities. Wireless sensor nodes are deployed in various pervasive computing applications to observe the happenings in the surroundings. Data gathered from such wireless sensor nodes are utilized for critical decision making in context-aware environment. The Frequent incorrect data sampling, missing values, untrustworthy data, misbehavior and selfishness of nodes are common in pervasive applications since they are deployed in unfriendly and harsh environment. Moreover, the increasing number of sensor node fabricator leads to interoperability problems in context aware pervasive applications because they are represented in different formats and processed using different techniques. In this paper, we propose an ontology based trust framework for sensor driven pervasive environment for evaluating node and data trustworthiness which suffers from heterogeneity and interoperability problems. The proposed approach is capable of handling all types of nodes in pervasive environment and heterogeneous data generated from harsh and unfriendly environments of context aware pervasive applications. The proposed method comprises of semantic sensor data model and an ontology which is written in OWL language and implemented in protege. The proposed ontology is validated against use case and used for finding the trustworthiness of different sensor nodes and its data using a generic TRUST ontology. © 2017 IEEE.Item Enhancing Knowledge Management in the Construction Industry: Exploring the Impact of Semantic Web Technologies(Springer Science and Business Media Deutschland GmbH, 2025) Kone, V.; Mahesh, G.; Ingle, P.V.This research paper investigates the practical applications of Semantic Web technologies within the construction industry, specifically focusing on their role in knowledge management. The methodology employed for this research entails a systematic literature review, wherein relevant studies pertaining to Semantic Web technologies in the construction industry are gathered and meticulously analyzed. The study’s findings provide valuable insights into the benefits, challenges, and opportunities associated with the implementation of Semantic Web technologies for knowledge management purposes. The research reveals that Semantic Web technologies play a vital role in facilitating enhanced knowledge discovery, integration, and retrieval within construction projects. By establishing interoperability and integrating diverse data sources, these technologies effectively break down data silos and enable a comprehensive view of project information. Moreover, the study demonstrates that Semantic Web technologies support efficient collaboration, improve decision-making processes, and enable advanced analytics and predictive capabilities within construction projects. The significance of this research paper lies in its contribution to the understanding of Semantic Web technologies and their potential to revolutionize knowledge management practices within the construction industry. In conclusion, this research paper highlights the transformative impact of Semantic Web technologies on knowledge management in construction, establishing a robust foundation for future research and practical implementation in this dynamic industry. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.