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Learning to extract and summarize hot item features from multiple auction web sites

Tak-Lam Wong, Wai Lam
2007 Knowledge and Information Systems  
We develop a unified framework which can automatically extract product features and summarize hot item features from multiple auction sites.  ...  To deal with the irregularity in the layout format of Web pages and harness the uncertainty involved, we formulate the tasks of product feature extraction and hot item feature summarization as a single  ...  Overview of our framework We develop a unified framework which can extract product features and discover hot item features from multiple auction Web sites collectively.  ... 
doi:10.1007/s10115-007-0078-2 fatcat:wleyivafdzd63kuex2spnd6n5q

Extracting and Summarizing Hot Item Features Across Different Auction Web Sites [chapter]

Tak-Lam Wong, Wai Lam, Shing-Kit Chan
2006 Lecture Notes in Computer Science  
We develop a unified framework aiming at automatically extracting the product features and summarizing the hot item features across different auction Web sites.  ...  , as well as various information such as the hot item features across different auction sites.  ...  Suppose we collect a set of Web pages from the auction Web sites and we wish to discover the hot item features.  ... 
doi:10.1007/11731139_39 fatcat:zlwijn3v25aatfjngchfkk2jf4

Research Directions, Challenges and Issues in Opinion Mining

Periakaruppan Sudhakaran, Shanmugasundaram Hariharan, Joan Lu
2013 International Journal of Advanced Science and Technology  
Rapid growth of Internet and availability of user reviews on the web for any product has provided a need for an effective system to analyze the web reviews.  ...  The opinions are retrieved from customers are based on three general formats.  ...  Acknowledgements The authors would like to express our special thanks to insightful suggestions for the anonymous reviewers.  ... 
doi:10.14257/ijast.2013.60.01 fatcat:vsb5anbrjfddvit64yw7tfk5q4

User Response Prediction in Online Advertising [article]

Zhabiz Gharibshah, Xingquan Zhu
2021 arXiv   pre-print
to products, purchases of items, or explicit user feedback through online surveys.  ...  How to predict user response in a reliable and/or transparent way?  ...  The information from publisher websites is usually obtained from crawling the web-pages to summarize the context.  ... 
arXiv:2101.02342v2 fatcat:clgefamcd5fmbeg5ephizy3zqu

Communal Service Delivery: How Customers Benefit from Participation in Firm-Hosted Virtual P3 Communities

Utpal M. Dholakia, Vera Blazevic, Caroline Wiertz, René Algesheimer
2009 Social Science Research Network  
Building upon the social constructivist view on learning and drawing from literature on the firm-customer relationship in services marketing, we distinguish between functional and social benefits received  ...  The proposed model is tested on data gathered from 2,299 active members of a P3 community hosted by a global online auction firm, and the framework's generalizability is demonstrated using a sample of  ...  Research Setting eBay is currently the world's largest online auction site. To participate in its auctions, buyers and sellers must learn to use eBay's trading platform effectively.  ... 
doi:10.2139/ssrn.1444828 fatcat:maa37rosgvai5ewdoax5ay7xui

Mining opinion components from unstructured reviews: A review

Khairullah Khan, Baharum Baharudin, Aurnagzeb Khan, Ashraf Ullah
2014 Journal of King Saud University: Computer and Information Sciences  
Accordingly, efficient computational methods are needed for mining and summarizing the reviews from corpuses and Web documents.  ...  Opinion mining is a way to retrieve information through search engines, Web blogs and social networks.  ...  Web mining refers to the implementation of text mining techniques for the purpose of extracting useful knowledge from Web text. OM is typically related to web mining.  ... 
doi:10.1016/j.jksuci.2014.03.009 fatcat:oma2lylgpzc7noalvewtsbtdqa

Communal Service Delivery

Utpal M. Dholakia, Vera Blazevic, Caroline Wiertz, René Algesheimer
2009 Journal of Service Research  
Building upon the social constructivist view on learning and drawing from literature on the firm-customer relationship in services marketing, we distinguish between functional and social benefits received  ...  The proposed model is tested on data gathered from 2,299 active members of a P3 community hosted by a global online auction firm, and the framework's generalizability is demonstrated using a sample of  ...  Research Setting eBay is currently the world's largest online auction site. To participate in its auctions, buyers and sellers must learn to use eBay's trading platform effectively.  ... 
doi:10.1177/1094670509338618 fatcat:ogiz3fagy5bqrgbsq5pcmziyzy

Netprobe

Shashank Pandit, Duen Horng Chau, Samuel Wang, Christos Faloutsos
2007 Proceedings of the 16th international conference on World Wide Web - WWW '07  
NetProbe models auction users and transactions as a Markov Random Field tuned to detect the suspicious patterns that fraudsters create, and employs a Belief Propagation mechanism to detect likely fraudsters  ...  Given a large online network of online auction users and their histories of transactions, how can we spot anomalies and auction fraud?  ...  We extracted features from auction data to capture fluctuations in sellers' behaviors (e.g., selling numerous expensive items after selling very few cheap items).  ... 
doi:10.1145/1242572.1242600 dblp:conf/www/PanditCWF07 fatcat:o2dxptvcd5dkfauehzpsi5lrde

Website features that gave rise to social commerce: a historical analysis

Renata Gonçalves Curty, Ping Zhang
2013 Electronic Commerce Research and Applications  
We were able to identify and classify a total of 174 emerging technical features.  ...  in 2007; and (3) there has been a significant effort to strengthen customer and merchant ties through relational features.  ...  R Mentoring Group and receive help from another eBay member on how to use eBay. Meet other new members and learn together. See: (web.archive.org/web/20071009122525/http://groups.eBay.com/index.jspa?  ... 
doi:10.1016/j.elerap.2013.04.001 fatcat:dzfq6hsw6ngkroqdu6dvbve7dy

DOMISA: DOM-based Information Space Adsorption for Web Information Hierarchy Mining [chapter]

Hung-Yu Kao, Jan-Ming Ho, Ming-Syan Chen
2004 Proceedings of the 2004 SIAM International Conference on Data Mining  
Consequently, we propose an information hierarchy in this paper, and, from that hierarchy, we can extract the significance and the relationship value of information contained within a Web page.  ...  Experiments on several commercial news Web sites show high precision and recall rates achieved by DOMISA in determining information clusters of pages which validates its practical applicability to Web  ...  In the first phase, we extract and aggregate useful features from the information of the DOM tree.  ... 
doi:10.1137/1.9781611972740.29 dblp:conf/sdm/KaoHC04 fatcat:jj7ojdq7grd4leo6tqzdzym4ji

Hot Item Mining and Summarization from Multiple Auction Web Sites

Tak-Lam Wong, Wai Lam
Fifth IEEE International Conference on Data Mining (ICDM'05)  
We develop a two-phase framework which aims at mining and summarizing hot items from multiple auction Web sites to assist decision making.  ...  The goal of the second phase is to discover and summarize the hot items based on the extracted information.  ...  The objective of the second phase is to mine and summarize hot items from multiple auction Web sites by making use of the extracted product features and feature values.  ... 
doi:10.1109/icdm.2005.78 dblp:conf/icdm/WongL05 fatcat:fte7p4ms25g3tix3w5n7ibsbne

:{unav)

Dimitrios Pierrakos, Georgios Paliouras, Christos Papatheodorou, Constantine D. Spyropoulos
2012 User modeling and user-adapted interaction  
This article views Web personalization through the prism of personalization policies adopted by Web sites and implementing a variety of functions.  ...  This issue is becoming increasingly important on the Web, as non-expert users are overwhelmed by the quantity of information available online, while commercial Web sites strive to add value to their services  ...  Acknowledgments We would like to thank the four anonymous reviewers and the editor for their constructive comments.  ... 
doi:10.1023/a:1026238916441 fatcat:p5hezimqczg4tos4vajivz23ea

Harnessing the Power of the General Public for Crowdsourced Business Intelligence: A Survey

Bin Guo, Yan Liu, Yi Ouyang, Vincent W. Zheng, Daqing Zhang, Zhiwen Yu
2019 IEEE Access  
Crowdsourced business intelligence (CrowdBI), which leverages the crowdsourced usergenerated data to extract useful knowledge about business and create marketing intelligence to excel in the business environment  ...  This paper first characterizes the concept model and unique features and presents a generic framework for CrowdBI.  ...  [24] extract four categories of features (i.e., linguistic features, product features, features extracted based on information quality and features extracted using information theory) to identify helpful  ... 
doi:10.1109/access.2019.2901027 fatcat:a5vz6vl7urckpdsreplkvjalea

A Systematic Survey of Online Data Mining Technology Intended for Law Enforcement

Matthew Edwards, Awais Rashid, Paul Rayson
2015 ACM Computing Surveys  
Such technologies must be well-designed and rigorously grounded, yet no survey of the online data-mining literature exists which examines their techniques, applications and rigour.  ...  article remedies this gap through a systematic mapping study describing online data mining literature which visibly targets law enforcement applications, using evidence-based practices in survey-making to  ...  [Zhou et al. 2005a ] briefly outline the motivation for and design of the Dark Web Portal, a resource used in several papers addressing information extraction from terrorist and extremist sites.  ... 
doi:10.1145/2811403 fatcat:qpvfebejpfgp5bh3cgykaoumze

Deep Learning for User Interest and Response Prediction in Online Display Advertising

Zhabiz Gharibshah, Xingquan Zhu, Arthur Hainline, Michael Conway
2020 Data Science and Engineering  
To achieve the goal, we collect page information displayed to the users as a temporal sequence and use long short-term memory (LSTM) network to learn features that represents user interests as latent features  ...  To date, existing methods for Ad click prediction, or click-through rate prediction, mainly consider representing users as a static feature set and train machine learning classifiers to predict clicks.  ...  from the copyright holder.  ... 
doi:10.1007/s41019-019-00115-y fatcat:mngwxyxd2jgbzkzp7menfchwm4
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