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A method for discovering the knowledge of item rank from consumer reviews. (English) Zbl 07037370
Summary: When observing a collection of ranked items, we may be interested in the questions of why and how one item is ranked over another. This paper presents a method for discovering the knowledge about the rank of the items from consumer reviews. We formulate the questions of interest as a single biconvex minimization problem which has a relationship with SVM (Support Vector Machines). To facilitate the process of knowledge discovery, we propose a two-stage learning algorithm for discovering knowledge from small data. Finally, we evaluate the method by showing our simulation and experiment results.
MSC:
68 Computer science
90 Operations research, mathematical programming
Software:
Python
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References:
[1] V. N. Vapnik, Statistical Learning Theory, John Wiley&Sons, New York, 1995. · Zbl 0833.62008
[2] G. Jochen; P. Frank; K. Kathrin, Biconvex sets and optimization with biconvex functions: a survey and extensions, Math. Meth. Oper. Res., 66, 373-407, (2007) · Zbl 1146.90495
[3] Goodreads Inc., Best Python programming books, http://www.goodreads.com/list/show/32685.
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