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Swot Analysis Of Hotel

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Words 1725
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SHANMUGHA
ARTS, SCIENCE, TECHNOLOGY & RESEARCH ACADEMY (SASTRA UNIVERSITY) SCHOOL OF COMPUTING

ANALYSIS ON WEB DATA-OPINION MINING

BATCH NO:07

GUIDED BY:Dr.B.SAN

ACKNOWLEDGEMENT

I have immense pleasure in expressing my heartfelt thanks to our Honourable Vice Chancellor Prof. R. Sethuraman for the benevolent advice and guidance during my tenure in the college. I wish to express my profound gratitude to Dr. S. Vaidhyasubramaniam, Dean of Planning & Development, Dr. S. Swaminathan, Director of CeNTAB and Prof. …show more content…
Which hotel should I stay? Which phone should I buy? These are some of the question which we face in our day today life. Where do we seek answer for it? Relatives, friends, neighbours, magazines, papers. But now a days it has been quite habit to check the world wide web for answer. Does searching the world wide web is easy the answer would be a big no. Why? Due to increase in the usage of world wide web lead to the increase in web data. So searching through the vast unclear data is difficult. This leads to the technique called opinion or sentiment analysis. The process extraction of useful information from the existing user reviews is called opinion mining. To achieve this we need to clean the data first which is a bit challenging task, since the writing varies from one user to another. The negative reviews may hold some positive points and vice versa we need to take that also into consideration to achieve proper …show more content…
Seed dependency pattern is used for extracting candidate features. These seed patterns along with the prior sentiment knowledge are applied to extract candidate features, and in turn these features can generate new dependency patterns.
Clustering algorithm is used to retain more infrequent features and form a more compact aspect structure .For a candidate feature , its most similar feature is found and grouped them together if their similarities larger than a threshold .In order to remove false features, weighting algorithm is used and the cluster with light ones is removed. They used positive-like adjectives (PAs) and negative-like adjectives(NA-s) for disambiguating sentiment orientations. Finally, clause sentiment analysis is performed to get the

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