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Implicit Feedback for Recommender System

by Douglas W. Oard, Jinmook Kim - Massachusetts Institute of Technology, Department of Electrical Engineering and Computer , 1998
"... Can implicit feedback substitute for explicit ratings in recommender systems? If so, we could avoid the difficulties associated with gathering explicit ratings from users. How, then, can we capture useful information unobtrusively, and how might we use that information to make recommendations? In th ..."
Abstract - Cited by 111 (8 self) - Add to MetaCart
Can implicit feedback substitute for explicit ratings in recommender systems? If so, we could avoid the difficulties associated with gathering explicit ratings from users. How, then, can we capture useful information unobtrusively, and how might we use that information to make recommendations

Collaborative filtering for implicit feedback datasets

by Yifan Hu, Yehuda Koren, Chris Volinsky - In IEEE International Conference on Data Mining (ICDM 2008 , 2008
"... A common task of recommender systems is to improve customer experience through personalized recommendations based on prior implicit feedback. These systems passively track different sorts of user behavior, such as purchase history, watching habits and browsing activity, in order to model user prefer ..."
Abstract - Cited by 193 (8 self) - Add to MetaCart
A common task of recommender systems is to improve customer experience through personalized recommendations based on prior implicit feedback. These systems passively track different sorts of user behavior, such as purchase history, watching habits and browsing activity, in order to model user

Implicit interest indicators

by Mark Claypool, Phong Le, Makoto Wased, David Brown - IN PROCEEDINGS OF IUI , 2001
"... Recommender systems provide personalized suggestions about items that users will find interesting. Typically, recommender systems require a user interface that can "intelligently" determine the interest of a user and use this information to make suggestions. The common solution, "expl ..."
Abstract - Cited by 231 (2 self) - Add to MetaCart
rating is obtained by a method other than obtaining it directly from the user. These implicit interest indicators have obvious advantages, including removing the cost of the user rating, and that every user interaction with the system can contribute to an implicit rating. Current recommender systems

BPR: Bayesian personalized ranking from implicit feedback

by Steffen Rendle, Christoph Freudenthaler, Zeno Gantner, Lars Schmidt-Thieme - IN: PROCEEDINGS OF THE 25TH CONFERENCE ON UNCERTAINTY IN ARTIFICIAL INTELLIGENCE (UAI , 2009
"... Item recommendation is the task of predicting a personalized ranking on a set of items (e.g. websites, movies, products). In this paper, we investigate the most common scenario with implicit feedback (e.g. clicks, purchases). There are many methods for item recommendation from implicit feedback like ..."
Abstract - Cited by 153 (17 self) - Add to MetaCart
Item recommendation is the task of predicting a personalized ranking on a set of items (e.g. websites, movies, products). In this paper, we investigate the most common scenario with implicit feedback (e.g. clicks, purchases). There are many methods for item recommendation from implicit feedback

Content-based, collaborative recommendation

by Marko Balabanović, Yoav Shoham - Communications of the ACM , 1997
"... By combining both collaborative and content-based filtering systems, Fab may eliminate many of the weaknesses found in each approach. ONLINE READERS ARE IN NEED OF TOOLS TO HELP THEM COPE with the mass of content available on the World-Wide Web. In traditional media, readers are provided assistance ..."
Abstract - Cited by 217 (0 self) - Add to MetaCart
in making selections. This includes both implicit assistance in the form of editorial oversight and explicit assistance in the form of recommendation services such as movie reviews and restaurant guides. The electronic medium offers new opportunities to create recommendation services, ones that adapt over

Hipikat: Recommending pertinent software development artifacts

by Davor Čubranić, Gail C. Murphy - In ICSE’03
"... A newcomer to a software project must typically come up-to-speed on a large, varied amount of information about the project before becoming productive. Assimilating this information in the open-source context is difficult because a newcomer cannot rely on the mentoring approach that is commonly used ..."
Abstract - Cited by 185 (5 self) - Add to MetaCart
used in traditional software developments. To help a newcomer to an open-source project become productive faster, we propose Hipikat, a tool that forms an implicit group memory from the information stored in a project’s archives, and that recommends artifacts from the archives that are relevant to a

Evaluating implicit measures to improve web search

by Steve Fox, Kuldeep Karnawat, Mark Mydland, Susan Dumais, Thomas White - ACM Transactions on Information Systems , 2005
"... Of growing interest in the area of improving the search experience is the collection of implicit user behavior measures (implicit measures) as indications of user interest and user satisfaction. Rather than having to submit explicit user feedback, which can be costly in time and resources and alter ..."
Abstract - Cited by 178 (5 self) - Add to MetaCart
Of growing interest in the area of improving the search experience is the collection of implicit user behavior measures (implicit measures) as indications of user interest and user satisfaction. Rather than having to submit explicit user feedback, which can be costly in time and resources and alter

Interactive Public Ambient Displays: Transitioning from Implicit to Explicit, Public to Personal, Interaction with Multiple Users

by Daniel Vogel, Ravin Balakrishnan - UIST , 2004
"... We develop design principles and an interaction framework for sharable, interactive public ambient displays that support the transition from implicit to explicit interaction with both public and personal information. A prototype system implementation that embodies these design principles is describe ..."
Abstract - Cited by 184 (5 self) - Add to MetaCart
We develop design principles and an interaction framework for sharable, interactive public ambient displays that support the transition from implicit to explicit interaction with both public and personal information. A prototype system implementation that embodies these design principles

A Contextual-Bandit Approach to Personalized News Article Recommendation

by Lihong Li, Wei Chu, John Langford, Robert E. Schapire
"... Personalized web services strive to adapt their services (advertisements, news articles, etc.) to individual users by making use of both content and user information. Despite a few recent advances, this problem remains challenging for at least two reasons. First, web service is featured with dynamic ..."
Abstract - Cited by 178 (16 self) - Add to MetaCart
with dynamically changing pools of content, rendering traditional collaborative filtering methods inapplicable. Second, the scale of most web services of practical interest calls for solutions that are both fast in learning and computation. In this work, we model personalized recommendation of news articles as a

A survey of methods and strategies in character segmentation

by Richard G. Casey, Eric Lecolinet - IEEE TRANSACTION ON PAMI , 1996
"... Character segmentation has long been a critical area of the OCR process. The higher recognition rates for isolated characters vs. those obtained for words and connected character strings well illustrate this fact. A good part of recent progress in reading unconstrained printed and written text may b ..."
Abstract - Cited by 212 (1 self) - Add to MetaCart
be ascribed to more insightful handling of segmentation. This paper provides a review of these advances. The aim is to provide an appreciation for the range of techniques that have been developed, rather than to simply list sources. Segmentation methods are listed under four main headings. What may be termed
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