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Sentiment is a terminology which define an attitude, opinion, thought, or perception that indicates ones feeling. Sentiment analysis correspondingly called as opinion mining, facilitates the extraction of individual’s sentiment towards certain elements. Now a days, social media applications like Twitter, Facebook etc. has an immense effect on individual lives as people post their thinking in form of posts on these applications. Researchers find Twitter to be the most commonly used social media application to post their opinions. Twitter is a microblogging sites in which a user send messages and those ongoing messages are called Tweets. But these sites carries various technical threats like noise, sparsity, non-standard vocabulary, multilingual content that is posted online. For tackling these challenges, the N-gram technique has been discussed which is used for feature extraction and Support Vector Machine (SVM) approach for classification for sentiment analysis. In this paper a brief introduction on Sentiment Analysis is given along with approaches and techniques. And a workflow on sentiment analysis technique also discussed.

Keywords

Sentiment Analysis, Opinion Mining, Social Media, N-Gram Technique, Support Vector Machine (SVM).

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References

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A Web Based Farmer Query System for the State of Jammu and Kashmir

Abstract Views :142 | PDF Views:0

Authors

Karam Singh ¹, Bhavna Arora ²

Affiliations
1 Department of Computer Science & IT, Central University of Jammu, Bagla, IN
2 Department Computer Science & IT, Central University of Jammu, Bagla, IN

Source

Research Cell: An International Journal of Engineering Sciences, Vol 27, No 1 (2018), Pagination: 69-77

Abstract

Agriculture is one of the most important pillars of Indian economy. Communication and information Technology (IT) can make Indian cultivation process better and can profit all people related with agri-business including land holders, marginalized poor agriculturist. To increase the productivity and quality of crops, the farmers often depend on agricultural advisors and experts to provide correct information for making decision for crop. Many times agricultural expert or advisors are not available all the time. This paper presents a review on the technologies which various researchers have used to provide agricultural advisory system based on specific question answering system. A brief description of the web based query processing system along with its workflow and process is also given. A comparative analysis of the recent models used in the literature is also presented in the paper.

Keywords

Web Services, Agri-Business, QANUS.

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References

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Prediction Analysis Techniques of Data Mining:A Review

Abstract Views :123 | PDF Views:2

Authors

Adeep Malmotra ¹, Bhavna Arora ¹

Affiliations
1 Department of Computer Science & IT, Central University, Jammu, IN

Source

Research Cell: An International Journal of Engineering Sciences, Vol 27, No 1 (2018), Pagination: 83-90

Abstract

The technique through which important information is extracted from the raw data in data sets is known as data mining. The future scenarios related to current data can be predicted with the help of prediction analysis technique provided under data mining. Clustering and classification forms the basis of prediction analysis. Numerous techniques have been proposed by various researchers in order to perform prediction analysis on various real-time applications. This paper describes the various techniques of prediction analysis proposed by various researchers. The paper also presents a review and analysis of these techniques based on parameters such as algorithms and techniques, datasets, attributes and tools used for analysis.

Keywords

Prediction Analysis, Classification, Clustering, K-Means, SVM (Support Vector Machine).

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References

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