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Biblioqrafik təsvir | Aliguliyev , R.M. QMOS: Query-based multi-documents opinion-oriented summarization / R.M. Aliguliyev // Information Processing and Management . - 2018. - N: 54. - P. 318-338. | Annotasiya | Sentiment analysis concerns the study of opinions expressed in a text. This paper presents the
QMOS method, which employs a combination of sentiment analysis and summarization approaches.
It is a lexicon-based method to query-based multi-documents summarization of opinion
expressed in reviews.
QMOS combines multiple sentiment dictionaries to improve word coverage limit of the individual
lexicon. A major problem for a dictionary-based approach is the semantic gap between
the prior polarity of a word presented by a lexicon and the word polarity in a specific context.
This is due to the fact that, the polarity of a word depends on the context in which it is being used.
Furthermore, the type of a sentence can also affect the performance of a sentiment analysis
approach. Therefore, to tackle the aforementioned challenges, QMOS integrates multiple strategies
to adjust word prior sentiment orientation while also considers the type of sentence. QMOS
also employs the Semantic Sentiment Approach to determine the sentiment score of a word if it is
not included in a sentiment lexicon.
On the other hand, the most of the existing methods fail to distinguish the meaning of a review
sentence and user"s query when both of them share the similar bag-of-words; hence there is often
a conflict between the extracted opinionated sentences and users" needs. However, the summarization
phase of QMOS is able to avoid extracting a review sentence whose similarity with the
user"s query is high but whose meaning is different. The method also employs the greedy algorithm
and query expansion approach to reduce redundancy and bridge the lexical gaps for similar
contexts that are expressed using different wording, respectively. Our experiment shows that the
QMOS method can significantly improve the performance and make QMOS comparable to other
existing methods. | Elektron variant | Elektron variant |
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