A Combinatorial Approach for Predicting Online Review Helpfulness of Indian Online Travel Agencies

Online user reviews are quite popular in social media, e-commerce and review websites. It is commonly referred as word of mouth which provides positive and negative messages from users about products and services. It helps users to get insights through review ratings and subjective feedback. As the volumes of reviews are high, it makes it harder for users to identify the helpfulness upfront. In general helpfulness rating is provided by the users who read the review, but many reviews still stay unrated. In this paper, we propose an approach of predicting helpfulness of such reviews from mouthshut.com using a combinatorial approach of empirical analysis and naïve Bayes machine learning method. The data set is chosen for Indian Online Travel Agencies (OTA) namely Makemytrip, Cleartrip, Yatra, Goibibo, and Expedia India. A detailed experiment is conducted and results are discussed by analyzing review metadata characteristics

Open Higher Education: Universities as leaders in open access

Universities are seats of higher education and research. Historically, most universities have been patronized and funded by governments. Most of the research and academic activities in most universities are essentially funded by public funds collected in the form of taxes. However much of the output of the research which is carried out in these universities is unfortunately in possession of commercial publishers. The ever increasing prices of scholarly journals and books have brought even the most resourceful libraries of the world to a saturation point. Libraries are no longer able to sustain subscriptions due to stagnant budgets on the one hand and high-cost of publications on the other. The paper discusses these issues and proposes that the Indian universities take up a leadership role in promoting open access to scholarly publications. This paper argues that it is the social responsibility of universities to encourage and implement open access to scholarly information produced by their respective faculty members and researchers

Trend of research on ontology: a study based on ProQuest and DART

Ontology is a broad term including a wide range of activities. It plays an important role in semantic web applications. This study is based on published Doctoral ETDs (Electronic Thesis and Dissertations) on ontology retrieved from two major ETD repositories ProQuest and DART. There were overall 2634 theses and dissertations in ProQuest and DART on ontology during last 10 years, from2003-2012. In ProQuest, majority of the theses are contributed by United States. There are theses on ontology in more than 20 variety languages. Regarding the productivity of institutions Tsinghai University is found to be the most productive Research institute involved on ontology research with reference to the ProQuest database. In DART, University of Southampton is the most productive research institute. Keyword analysis shows that the most prominent keywords are Ontology, Metaphysics, Semantic Web, Phenomenology and Artificial Intelligence

Managing Language Diversity Across Cultures: the English-Mongolian Case Study

Developing ontologies from scratch appears to be very expensive in terms of cost and time required and often such efforts remain unfinished for decades. Ontology localization through translation seems to be a promising approach towards addressing this issue as it enables the greater reuse of the ontological (backbone) structure. However, managing language diversity across cultures remains as a challenge that has to be taken into account and dealt with right level of attention and expertise. In this paper we report the result of our experiment that was performed with approximately 1000 concepts, taken from the space ontology originally developed in English, by providing their ranslation into Mongolian

Social Computing Platforms Leveraging Knowledge Flow Patterns

The loss of tacit knowledge, inability to capture and re use knowledge and lack of structured workspace collaboration are frequently faced challenges in organizations. The change in knowledge sourcing behaviors by the current generation workforce has impacted the knowledge flow patterns in organizations. The paper attempts to analyze the impact of existing knowledge flow patterns in an organization and identify means to improve the effectiveness of knowledge sharing initiatives in the organization via social computing platforms. Use of social computing platforms enables efficient workspace collaboration. As part of this study, customized solutions are calibrated based on knowledge flow patterns prevalent in teams. Knowledge Network Analysis (KNA) is a sociometric analysis performed to identify knowledge flow patterns and interactions among people in a team. The outcomes of the KNA describe the relationships between team members and knowledge flows. KNA showcases the communication ties prevalent in teams and interactions between human and system resources. The results of these analyses are used to identify push and pull networks which in turn enable effective knowledge management. Results of this study reveal that analyzing the knowledge flow patterns in a team and deploying a customized social computing platform that is tailored to address the specific knowledge flow patterns within that team significantly enhances the impact as opposed to a standardized “one-size-fits-all” platform. Impacts seen include a significant change in knowledge sourcing behaviors, resulting in capture of the tacit knowledge of employees, which further results in reducing the impact of employee movements & attrition. For instance, targeted Communities of Practice based on the presence of cliques in knowledge flow patterns within teams enabled the teams to be able to complete projects efficiently and sustain the quality of deliverables

Ontology and Inference Rules for Semantic Web based Applications

The minimum requirement of the Semantic Web applications in a Semantic Web technology is to create the ontology and RDF triple database. The Semantic Web based applications can make the use of its languages and technologies especially to those related to ontology. The ontology expresses the explicit knowledge of domain that the machine can understand and use the web ontology language like RDF, RDFS and OWL etc. and expression of description logics. In order to develop the Semantic Web based applications, we introduce how the ontology and inference rules can be applied in Semantic Web applications. The inference based ontology shows the excellent performance and intelligent use of information for Semantic Web applications. As a case study, we have discussed the construction of ontology for university system to verify the concepts of ontology and inference rules which uses the technologies of both ontology and their rules to establish the knowledge base for the university