Abstract-Opinion mining is an interesting area of research because of its wide applications in the decision-making process. Opinion mining aims to extract user's perception from the text and to create a fast and accurate summary of people's opinion about anything. In this study, we have worked on opinion target identification and the impact of anaphora resolution on opinion target extraction. Anaphora resolution can be utilized to detect opinion target in sentences having prepositions instead of nouns. We empirically evaluated the impact of anaphora resolution using benchmark datasets. We have achieved accuracy such as precision: 88.14 recall: 71.45 and f-score: 72.12, respectively.
The volume of data on the web is growing rapidly, due to the proliferation of news sources, contents, blogs and journals etc. Like other languages, the Urdu language has also observed tremendous growth on the internet. As the volume of data is expanding, information retrieval (IR) is becoming complicated. Document clustering is an unsupervised ML approach, employed to group a huge number of dispersed documents into a small number of significant and consistent clusters, thus providing a base for indexing, IR and browsing mechanisms. Documents clustering has a long tradition in English as well as English like western languages, but Urdu lags behind in terms sophisticated natural language processing (NLP) tools and resources for documents clustering. Documents clustering becomes a challenging task in Urdu language having a rich morphology, particular structure, syntax peculiarities and cursive nature. In this study, we have developed a framework of document clustering and analysed various similarity measures for Urdu documents. We have also checked the effect of stop words removal in the process of Urdu document clustering.
Internet is the most significant source of getting up thoughts, surveys for a product, and reviews for any type of service or activity. A Bulky amount of reviews are produced on daily basis on the cyberspace about online products and objects. For example, many individuals share their remarks, reviews and feelings in their own language utilizing social media networks such as twitter and so on. Considering their colossal Quantity and size, it is exceedingly knotty to look at with and interpret specified surveys. Sentiment Analysis (SA) aims at extracting people's opinion, felling and thought from their reviews in social websites. SA has recently gained significant consideration, however the vast majority of the resources and frameworks constructed so far are tailored to English as well as English like Western languages. The requirement for designing frameworks for different dialects is expanding, particularly as blogging and micro-blogging sites are becoming popular. This paper presents a comprehensive review of approaches of Urdu sentiment analysis and outlines of relevant gaps in the literature.
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