361,073 research outputs found
Research Directions, Challenges and Issues in Opinion Mining
Rapid growth of Internet and availability of user reviews on the web for any product has provided a need for an effective system to analyze the web reviews. Such reviews are useful to some extent, promising both the customers and product manufacturers. For any popular product, the number of reviews can be in hundreds or even thousands. This creates difficulty for a customer to analyze them and make important decisions on whether to purchase the product or to not. Mining such product reviews or opinions is termed as opinion mining which is broadly classified into two main categories namely facts and opinions. Though there are several approaches for opinion mining, there remains a challenge to decide on the recommendation provided by the system. In this paper, we analyze the basics of opinion mining, challenges, pros & cons of past opinion mining systems and provide some directions for the future research work, focusing on the challenges and issues
A Machine Learning Approach For Opinion Holder Extraction In Arabic Language
Opinion mining aims at extracting useful subjective information from reliable
amounts of text. Opinion mining holder recognition is a task that has not been
considered yet in Arabic Language. This task essentially requires deep
understanding of clauses structures. Unfortunately, the lack of a robust,
publicly available, Arabic parser further complicates the research. This paper
presents a leading research for the opinion holder extraction in Arabic news
independent from any lexical parsers. We investigate constructing a
comprehensive feature set to compensate the lack of parsing structural
outcomes. The proposed feature set is tuned from English previous works coupled
with our proposed semantic field and named entities features. Our feature
analysis is based on Conditional Random Fields (CRF) and semi-supervised
pattern recognition techniques. Different research models are evaluated via
cross-validation experiments achieving 54.03 F-measure. We publicly release our
own research outcome corpus and lexicon for opinion mining community to
encourage further research
Sentiment Analysis Using Collaborated Opinion Mining
Opinion mining and Sentiment analysis have emerged as a field of study since
the widespread of World Wide Web and internet. Opinion refers to extraction of
those lines or phrase in the raw and huge data which express an opinion.
Sentiment analysis on the other hand identifies the polarity of the opinion
being extracted. In this paper we propose the sentiment analysis in
collaboration with opinion extraction, summarization, and tracking the records
of the students. The paper modifies the existing algorithm in order to obtain
the collaborated opinion about the students. The resultant opinion is
represented as very high, high, moderate, low and very low. The paper is based
on a case study where teachers give their remarks about the students and by
applying the proposed sentiment analysis algorithm the opinion is extracted and
represented.Comment: 5 pages, 6 figure
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