Context-aware recommender systems (CARS) generate more relevant recommendations by adapting them to the specific contextual situation of the user. This article explores how contextual information can be used to create more intelligent and useful recommender systems. It provides an overview of the multifaceted notion of context, discusses several approaches for incorporating contextual information in recommendation process, and illustrates the usage of such approaches in several application areas where different types of contexts are exploited. The article concludes by discussing the challenges and future research directions for context-aware recommender systems.
Requirements engineering in large-scaled industrial, government, and international projects can be a highly complex process involving thousands, or even hundreds of thousands of potentially distributed stakeholders. As a result, many human intensive tasks in requirements elicitation, analysis, and management processes can be augmented and supported through the use of recommender system and machine learning techniques. In this article we describe several areas in which recommendation technologies have been applied to the requirements engineering domain, namely stakeholder identification, domain analysis, requirements elicitation, and decision support across several requirements analysis and prioritization tasks. We also highlight ongoing challenges and opportunities for applying recommender systems in the requirements engineering domain.
Bunescu, Razvan C (Ohio University) | Carvalho, Vitor R. (Microsoft Live Labs) | Chomicki, Jan (University of Buffalo) | Conitzer, Vincent (Duke University) | Cox, Michael T. (BBN Technologies) | Dignum, Virginia (Utrecht University) | Dodds, Zachary (Harvey Mudd College) | Dredze, Mark (University of Pennsylvania) | Furcy, David (University of Wisconsin Oshkosh) | Gabrilovich, Evgeniy (Yahoo! Research) | Göker, Mehmet H. (PricewaterhouseCoopers) | Guesgen, Hans Werner (Massey University) | Hirsh, Haym (Rutgers University) | Jannach, Dietmar (Dortmund University of Technology) | Junker, Ulrich (ILOG) | Ketter, Wolfgang (Erasmus University) | Kobsa, Alfred (University of California, Irvine) | Koenig, Sven (University of Southern California) | Lau, Tessa (IBM Almaden Research Center) | Lewis, Lundy (Southern New Hampshire University) | Matson, Eric (Purdue University) | Metzler, Ted (Oklahoma City University) | Mihalcea, Rada (University of North Texas) | Mobasher, Bamshad (DePaul University) | Pineau, Joelle (McGill University) | Poupart, Pascal (University of Waterloo) | Raja, Anita (University of North Carolina at Charlotte) | Ruml, Wheeler (University of New Hampshire) | Sadeh, Norman M. (Carnegie Mellon University) | Shani, Guy (Microsoft Research) | Shapiro, Daniel (Applied Reactivity, Inc.) | Singh, Sarabjot Anand (University of Warwick) | Taylor, Matthew E. (University of Southern California) | Wagstaff, Kiri (Jet Propulsion Laboratory) | Smith, Trey (Carnegie Mellon University West) | Walsh, William (CombineNet) | Zhou, Ron (Palo Alto Research Center)
The program included the following fifteen workshops: Advancements in POMDP Solvers, AI Education Workshop, Coordination, Organization, Institutions and Norms in Agent Systems, Enhanced Messaging, Human Implications of Human-Robot Interaction, Intelligent Techniques for Web Personalization and Recommender Systems, Metareasoning: Thinking about Thinking, Multidisciplinary Workshop on Advances in Preference Handling, Search in Artificial Intelligence and Robotics, Spatial and Temporal Reasoning, Trading Agent Design and Analysis, Transfer Learning for Complex Tasks, What Went Wrong and Why: Lessons from AI Research and Applications, and Wikipedia and Artificial Intelligence: An Evolving Synergy. The goal of the Coordination, Organizations, Institutions and Norms in Multiagent Systems workshop was to examine and define the current state of the art research in agent systems research related to coordination, organizations institutions and norming. The Intelligent Techniques for Web Personalization and Recommender Systems workshop was scheduled as a joint event, bringing together researchers and practitioners from the fields of web personalization and recommender systems. The Search in Artificial Intelligence and Robotics workshop brought together search researchers to share their ideas and disseminate their latest research results.
Anand, Sarabjot Singh, Bahls, Daniel, Burghart, Catherina R., Burstein, Mark, Chen, Huajun, Collins, John, Dietterich, Tom, Doyle, Jon, Drummond, Chris, Elazmeh, William, Geib, Christopher, Goldsmith, Judy, Guesgen, Hans W., Hendler, Jim, Jannach, Dietmar, Japkowicz, Nathalie, Junker, Ulrich, Kaminka, Gal A., Kobsa, Alfred, Lang, Jerome, Leake, David B., Lewis, Lundy, Ligozat, Gerard, Macskassy, Sofus, McDermott, Drew, Metzler, Ted, Mobasher, Bamshad, Nambiar, Ullas, Nie, Zaiqing, Orsvarn, Klas, O'Sullivan, Barry, Pynadath, David, Renz, Jochen, Rodriguez, Rita V., Roth-Berghofer, Thomas, Schulz, Stefan, Studer, Rudi, Wang, Yimin, Wellman, Michael
The AAAI-07 workshop program was held Sunday and Monday, July 22-23, in Vancouver, British Columbia, Canada. The program included the following thirteen workshops: (1) Acquiring Planning Knowledge via Demonstration; (2) Configuration; (3) Evaluating Architectures for Intelligence; (4) Evaluation Methods for Machine Learning; (5) Explanation-Aware Computing; (6) Human Implications of Human-Robot Interaction; (7) Intelligent Techniques for Web Personalization; (8) Plan, Activity, and Intent Recognition; (9) Preference Handling for Artificial Intelligence; (10) Semantic e-Science; (11) Spatial and Temporal Reasoning; (12) Trading Agent Design and Analysis; and (13) Information Integration on the Web.
Achtner, Wolfgang, Aimeur, Esma, Anand, Sarabjot Singh, Appelt, Doug, Ashish, Naveen, Barnes, Tiffany, Beck, Joseph E., Dias, M. Bernardine, Doshi, Prashant, Drummond, Chris, Elazmeh, William, Felner, Ariel, Freitag, Dayne, Geffner, Hector, Geib, Christopher W., Goodwin, Richard, Holte, Robert C., Hutter, Frank, Isaac, Fair, Japkowicz, Nathalie, Kaminka, Gal A., Koenig, Sven, Lagoudakis, Michail G., Leake, David B., Lewis, Lundy, Liu, Hugo, Metzler, Ted, Mihalcea, Rada, Mobasher, Bamshad, Poupart, Pascal, Pynadath, David V., Roth-Berghofer, Thomas, Ruml, Wheeler, Schulz, Stefan, Schwarz, Sven, Seneff, Stephanie, Sheth, Amit, Sun, Ron, Thielscher, Michael, Upal, Afzal, Williams, Jason, Young, Steve, Zelenko, Dmitry
The Workshop program of the Twenty-First Conference on Artificial Intelligence was held July 16-17, 2006 in Boston, Massachusetts. The program was chaired by Joyce Chai and Keith Decker. The titles of the 17 workshops were AIDriven Technologies for Service-Oriented Computing; Auction Mechanisms for Robot Coordination; Cognitive Modeling and Agent-Based Social Simulations, Cognitive Robotics; Computational Aesthetics: Artificial Intelligence Approaches to Beauty and Happiness; Educational Data Mining; Evaluation Methods for Machine Learning; Event Extraction and Synthesis; Heuristic Search, Memory- Based Heuristics, and Their Applications; Human Implications of Human-Robot Interaction; Intelligent Techniques in Web Personalization; Learning for Search; Modeling and Retrieval of Context; Modeling Others from Observations; and Statistical and Empirical Approaches for Spoken Dialogue Systems.
Muslea, Ion, Dignum, Virginia, Corkill, Daniel, Jonker, Catholijn, Dignum, Frank, Coradeschi, Silvia, Saffiotti, Alessandro, Fu, Dan, Orkin, Jeff, Cheetham, William E., Goebel, Kai, Bonissone, Piero, Soh, Leen-Kiat, Jones, Randolph M., Wray, Robert E., Scheutz, Matthias, Farias, Daniela Pucci de, Mannor, Shie, Theocharou, Georgios, Precup, Doina, Mobasher, Bamshad, Anand, Sarabjot Singh, Berendt, Bettina, Hotho, Andreas, Guesgen, Hans, Rosenstein, Michael T., Ghavamzadeh, Mohammad
AAAI presented the AAAI-04 workshop program on July 25-26, 2004 in San Jose, California. This program included twelve workshops covering a wide range of topics in artificial intelligence. The titles of the workshops were as follows: (1) Adaptive Text Extraction and Mining; (2) Agent Organizations: Theory and Practice; (3) Anchoring Symbols to Sensor Data; (4) Challenges in Game AI; (5) Fielding Applications of Artificial Intelligence; (6) Forming and Maintaining Coalitions in Adaptive Multiagent Systems; (7) Intelligent Agent Architectures: Combining the Strengths of Software Engineering and Cognitive Systems; (8) Learning and Planning in Markov Processes -- Advances and Challenges; (9) Semantic Web Personalization; (10) Sensor Networks; (11) Spatial and Temporal Reasoning; and (12) Supervisory Control of Learning and Adaptive Systems.