Product ranking using hierarchical aspect structures

Product-related comparative reviews are one of the most helpful information sources for consumers to rank the competing products and make purchase decisions. The comparative reviews are even more valuable if they are concerning specific aspects. However, the fact that very few comparative reviews express direct opinions on product aspects makes aspect-based product ranking a difficult task. In this paper, we present a novel hierarchical aspect-based product ranking approach. We first mine aspect-based pairwise comparative opinions from both user reviews on multiple review websites and community-based question answering pairs containing product comparison information. Next, we use our hierarchical structure-based model to propagate and reassign the aspect-based comparative opinions by using the parent-child and sibling relations between aspects in the product aspect hierarchy. The structure-based model helps to address the data sparsity issue of very few or no comparative reviews for some aspects. Finally, we employ graph-based ordering algorithms to consolidate these reassigned pairwise opinions into listwise comparison results. Experiments on a set of candidate electronic products prove that the proposed approach is effective for aspect-based product ranking.

[1]  Bing Liu,et al.  Mining Comparative Sentences and Relations , 2006, AAAI.

[2]  Youngjoong Ko,et al.  Extracting Comparative Entities and Predicates from Texts Using Comparative Type Classification , 2011, ACL.

[3]  Bing Liu.  Sentiment Analysis and Opinion Mining Opinion Mining , 2011 .

[4]  Meng Wang,et al.  Product comparison using comparative relations , 2011, SIGIR.

[5]  Xuanjing Huang,et al.  Mining product reviews based on shallow dependency parsing , 2009, SIGIR.

[6]  Jianshu Sun,et al.  Mining Reviews for Product Comparison and Recommendation , 2009, Polytech. Open Libr. Int. Bull. Inf. Technol. Sci..

[7]  Chun Chen,et al.  Opinion Word Expansion and Target Extraction through Double Propagation , 2011, CL.

[8]  M. Kendall.  A NEW MEASURE OF RANK CORRELATION , 1938 .

[9]  Tat-Seng Chua,et al.  Unsupervised learning of soft patterns for generating definitions from online news , 2004, WWW '04.

[10]  J. Keziya Rani,et al.  Mining Opinion Features in Customer Reviews. , 2016 .

[11]  Zhoujun Li,et al.  Comparable Entity Mining from Comparative Questions , 2010, ACL.

[12]  Meng Wang,et al.  Product Aspect Ranking and Its Applications , 2014, IEEE Transactions on Knowledge and Data Engineering.

[13]  Martin Ester,et al.  ILDA: interdependent LDA model for learning latent aspects and their ratings from online product reviews , 2011, SIGIR.

[14]  Philip S. Yu,et al.  A holistic lexicon-based approach to opinion mining , 2008, WSDM '08.

[15]  Arjun Mukherjee,et al.  Aspect Extraction with Automated Prior Knowledge Learning , 2014, ACL.

[16]  Kai Wang,et al.  Prototype hierarchy based clustering for the categorization and navigation of web collections , 2010, SIGIR.

[17]  Claire Cardie,et al.  Annotating Expressions of Opinions and Emotions in Language , 2005, Lang. Resour. Evaluation.

[18]  Oren Etzioni,et al.  Extracting Product Features and Opinions from Reviews , 2005, HLT.

[19]  Yoram Singer,et al.  Learning to Order Things , 1997, NIPS.

[20]  Bing Liu,et al.  Sentiment Analysis and Opinion Mining , 2012, Synthesis Lectures on Human Language Technologies.

[21]  A. Choudhary,et al.  Mining millions of reviews: a technique to rank products based on importance of reviews , 2011, ICEC '11.

[22]  Bo Pang,et al.  Thumbs up? Sentiment Classification using Machine Learning Techniques , 2002, EMNLP.

[23]  Yoshua Bengio,et al.  Domain Adaptation for Large-Scale Sentiment Classification: A Deep Learning Approach , 2011, ICML.

[24]  Himabindu Lakkaraju,et al.  Exploiting Coherence for the Simultaneous Discovery of Latent Facets and associated Sentiments , 2011, SDM.

[25]  Vasudeva Varma,et al.  An Unsupervised Approach to Product Attribute Extraction , 2009, ECIR.

[26]  Qian Liu,et al.  A Logic Programming Approach to Aspect Extraction in Opinion Mining , 2013, 2013 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT).

[27]  A. Arunkarthi,et al.  Aspect-Based Opinion Mining from Online Reviews , 2016 .

[28]  Peng Jiang,et al.  An Approach Based on Tree Kernels for Opinion Mining of Online Product Reviews , 2010, 2010 IEEE International Conference on Data Mining.

[29]  Olfa Nasraoui,et al.  Web data mining: exploring hyperlinks, contents, and usage data , 2008, SKDD.

[30]  Bing Liu,et al.  Identifying comparative sentences in text documents , 2006, SIGIR.

[31]  Meng Wang,et al.  Aspect Ranking: Identifying Important Product Aspects from Online Consumer Reviews , 2011, ACL.

[32]  Alok N. Choudhary,et al.  Voice of the Customers: Mining Online Customer Reviews for Product Feature-based Ranking , 2010, WOSN.

[33]  Soo-Min Kim,et al.  Automatically Assessing Review Helpfulness , 2006, EMNLP.

[34]  Soo-Min Kim,et al.  Determining the Sentiment of Opinions , 2004, COLING.

[35]  Andrea Esuli,et al.  SENTIWORDNET: A Publicly Available Lexical Resource for Opinion Mining , 2006, LREC.

[36]  Lillian Lee,et al.  Opinion Mining and Sentiment Analysis , 2008, Found. Trends Inf. Retr..

[37]  Zhen Hai,et al.  Implicit Feature Identification via Co-occurrence Association Rule Mining , 2011, CICLing.

[38]  Lei Zhang,et al.  Sentiment Analysis and Opinion Mining , 2017, Encyclopedia of Machine Learning and Data Mining.

[39]  Bing Liu,et al.  Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data , 2006, Data-Centric Systems and Applications.

[40]  Jon Atle Gulla,et al.  Sentiment Learning on Product Reviews via Sentiment Ontology Tree , 2010, ACL.

[41]  Martin Ester,et al.  Aspect-based opinion mining from product reviews , 2012, SIGIR '12.

[42]  Rohini K. Srihari,et al.  OpinionMiner: a novel machine learning system for web opinion mining and extraction , 2009, KDD.

[43]  Bing Liu,et al.  Opinion observer: analyzing and comparing opinions on the Web , 2005, WWW '05.

[44]  Bing Liu,et al.  Mining Opinions in Comparative Sentences , 2008, COLING.

[45]  Hao Yu,et al.  Structure-Aware Review Mining and Summarization , 2010, COLING.