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Guest editorial: content, concept and context mining in social media
2011
World wide web (Bussum)
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probabilistic approaches for recommender system development in the presence of "words of few mouths". ...
., titled "Opinion Helpfulness Prediction in the Presence of Words of Few Mouths", identifies a widely existing phenomenon in social media content called the "words of few mouths" phenomenon and proposes ...
doi:10.1007/s11280-011-0142-4
fatcat:lzq4xr5lwzecjdtikt3kbc7sjm
Probabilistic Approaches to Consumer-generated Review Recommendation
2011
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Our entropy-based approach is relatively simple and suitable for applications requiring simple recommendation engine with fully-voted reviews. ...
Recommender Systems from "Words of Few Mouths". ...
"words of few mouths". ...
doi:10.20381/ruor-4553
fatcat:urzaslrhxnhennhrxnnbxrtnse
An Interactive Network for End-to-End Review Helpfulness Modeling
2020
Data Science and Engineering
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The sameness detection follows [25] by examining whether two reviews share more than 80% of their bigram occurrences. (3) To alleviate biases caused by the "words of few mouths" [53, 67] phenomenon ...
From a practical perspective, TRI can be hopefully integrated into existing helpfulness prediction systems. ...
material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from ...
doi:10.1007/s41019-020-00133-1
fatcat:xk7cl6mdsnbshhyzhodl43pvpa
Feature selection for helpfulness prediction of online product reviews: An empirical study
2019
PLoS ONE
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To this end, the 30 most frequently used content-based features are first identified from 149 relevant research papers and grouped into five coherent categories. ...
of few mouths [114] ; and (4) the remaining reviews are lowercased, tokenized, and the articles are removed. ...
In the deluge of data, to identify and recommend the informative reviews, rather than those of random quality is an important task. ...
doi:10.1371/journal.pone.0226902
pmid:31869404
fatcat:urf53eblg5c3rcs4ep7fd6ob7e