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Sharma, Neeraj
- PuDO:Development of an Ontology for Hierarchical Organization and Representation of Domains for Punjabi Words
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Authors
Affiliations
1 Department of Computer Science, Punjabi University, Patiala, IN
1 Department of Computer Science, Punjabi University, Patiala, IN
Source
Research Cell: An International Journal of Engineering Sciences, Vol 19 (2016), Pagination: 55-61Abstract
(Natural Language Processing (NLP) is the area of research which focuses on the different tasks of understanding, extraction and retrieval from unstructured text. It makes use of multiple tools, resources and methodologies for performing these tasks. NLP applications developed depend heavily upon resources apart from tools and methodologies. Like many other Indian languages, Punjabi language also inherits a rich literature history but on technological aspects it is relatively under resourced and still a lot of work remains to be done in the field of Punjabi language processing. There are many researchers, groups and organizations which are working on the different aspects of Punjabi language processing but it does not have many NLP resources of its own, such as, annotated corpora, rich dictionaries, sentiment lexicons, conceptualized domains etc.
Our present work is an attempt to develop a controlled vocabulary of concepts or topics (domains) for Punjabi words and present it in the form of 'domains ontology', PUDO (Punjabi Domains Ontology). Ontologies capture and describe the current state of knowledge about a domain of interest, and represent it in terms of concepts and relationships in ways that computers can process efficiently and humans can understand easily. This paper presents our work which is based on identifying the concepts termed as domains for Punjabi language words which can be organized in a hierarchical manner. The hierarchy is based on relation of specificity for Punjabi language. We developed the domains ontology by starting assigning concepts as top level domains and then conceptualized lower level domains having more granular conceptualization under the higher level domains. The developed ontology is further populated with the words as instances which evoke these domains. This developed resource can further be used in different semantically based NLP tasks in Punjabi language.
Keywords
Domains, Ontology, Semantics, Natural Language Processing, NLP, Punjabi NLP.Full Text
- Can Managing Knowledge and Experience Improve Software Process? - Insights from the Literature
Abstract Views :90 |
PDF Views:6
Authors
Affiliations
1 Department of Computer Science, University Computer Centre, Punjabi University, Patiala - 147002, IN
2 University Computer Centre, Punjabi University, Patiala - 147002, IN
3 Management Development Institute, Gurgaon - 122007, IN
1 Department of Computer Science, University Computer Centre, Punjabi University, Patiala - 147002, IN
2 University Computer Centre, Punjabi University, Patiala - 147002, IN
3 Management Development Institute, Gurgaon - 122007, IN
Source
Research Cell: An International Journal of Engineering Sciences, Vol 4 (2011), Pagination: 324-333Abstract
The field of knowledge management has gained wide attention across all industry sectors including software development. Managing accumulated knowledge and experiences of members of software engineering community is seen as a silver bullet to end many of the classical ills associated with the art of software development. Knowledge and experience management is also advocated in improving software development process. The present paper investigates the role of knowledge and experience management in improving the software process.Keywords
Knowledge Management, Experience Management, Software Process Improvement, Experience Factory.Full Text
- What Makes or Mars a Knowledge Based Software Process Improvement Initiative?-Prescriptions from
Abstract Views :100 |
PDF Views:2
Authors
Affiliations
1 Department of Computer Science, Punjabi University, Patiala - 147002, IN
2 University Computer Centre, Punjabi University, Patiala - 147002, IN
3 Management Development Institute, Gurgaon - 122007, IN
1 Department of Computer Science, Punjabi University, Patiala - 147002, IN
2 University Computer Centre, Punjabi University, Patiala - 147002, IN
3 Management Development Institute, Gurgaon - 122007, IN
Source
Research Cell: An International Journal of Engineering Sciences, Vol 1 (2011), Pagination: 283-302Abstract
Software product quality has always been the most desired thing in the field of software engineering. Software quality is directly related to the software development process. Various models of quality improvement proposed by SEI have been serving as great guides in this direction but recently the whole area of Software Process Improvement has got wide attention of software engineers and researchers alike. Though there are many models proposed in the literature for the implementation of knowledge based SPI, there is dearth of consensus on what makes the SPI effort a success. The present paper explores the critical factors of success as prescribed in literature for the successful implementation of knowledge based SPI.
Full Text
- Analysis of Some Popularly Used Techniques of Click Stream Analysis
Abstract Views :144 |
PDF Views:0
Authors
Affiliations
1 Department of Computer Science, Punjabi University, Patiala, IN
2 University Computer Centre, Punjabi University, Patiala, IN
1 Department of Computer Science, Punjabi University, Patiala, IN
2 University Computer Centre, Punjabi University, Patiala, IN
Source
Research Cell: An International Journal of Engineering Sciences, Vol 26 (2017), Pagination: 193-201Abstract
Websites and other online business marketing are becoming more effective and powerful way to deal and interact with users. The research study focuses on the working and techniques of click-stream analysis. Click-Stream Analysis is a comprehensive body of data that is used for describing the sequences of all the activities that have been happened between a user's browser and the other internet resource like a website and a third party ad server. The website chosen www.indiatourandtrip.com which is used for knowing the interest of the customers so that we can enhance the business and make it better. We have used data mining techniques for the extraction of valuable data, this data have been taken in order to predict the users behaviour and their interest. The research study focus on different classifiers and the performance evaluation of each classifier is done to get better results. The main motive of this evaluation is to upgrade the tour and travel site in order to make it more convenient for booking the tour packages and hotel on reasonable value price and it’s the effective way to optimize the website for the improvement of the booking and marketing with the help of software called MATLAB.Full Text
References
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- Missing Value Treatment using Effective Optimization on Data from Multiple Social Media
Abstract Views :213 |
PDF Views:0
Authors
Affiliations
1 Department of Computer Science, Punjabi University, Patiala, Punjab, IN
2 University Computer Center, Punjabi University, Patiala, Punjab, IN
1 Department of Computer Science, Punjabi University, Patiala, Punjab, IN
2 University Computer Center, Punjabi University, Patiala, Punjab, IN
Source
Research Cell: An International Journal of Engineering Sciences, Vol 30, No SP (2018), Pagination: 135-147Abstract
Missing value are broad in numerous genuine applications. Missing value imputation and in addition treatment is vital on the grounds that the skipping of missing value based records can harm the general results. For instance, if the client conclusions about information leak in India are fetched from social media then the client having hidden personal information can be covered in missing records. Such records cannot be skipped because of the privacy concerns of the users and therefore missing value imputation should be implemented on such records. In this research work, random forest approach for missing value imputation is devised and implemented on the different types of social media like youtube, twitter, tumblr.Keywords
Social Media, Random Forest Approach, Missing Value, Missing Value Imputation.Full Text
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