Iterative Relevance Feedback with Adaptive Exploration/Exploitation Trade-off
Publications associées (88)
Graph Chatbot
Chattez avec Graph Search
Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.
AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.
Mobile service robots are going to play an increasing role in the society of humans. Voice-enabled interaction with service robots becomes very important, if such robots are to be deployed in real-world environments and accepted by the vast majority of pot ...
This work presents a discriminative model for the retrieval of pictures from text queries. The core idea of this approach is to minimize a loss directly related to the retrieval performance of the model. For that purpose, we rely on a ranking loss which ha ...
We consider example-critiquing systems that help people search for their most preferred item in a large electronic catalog. We analyze how such systems can help users in the framework of four existing example-critiquing approaches (RABBIT, FindMe, Incremen ...
In a previously reported user study, we found that users were able to perform decision tradeoff tasks more efficiently and commit considerably fewer errors with the example critiquing interface than with the ranked list. We concluded that example-based sea ...
Association for Computing Machinery, New York, NY 10036-5701, United States2005
Decentralized and unstructured networks are becoming more prevalent today (e.g. ad hoc networks). Like every network, they depend on the cooperation of their users to survive. However, each user does not necessarily know who the others are, or what their i ...
We consider example-critiquing systems that help people search for their most preferred item in a large catalog. We compare 6 existing approaches in terms of user or system-centric, implicit or explicit use of preferences, assumptions used and their behavi ...
This work presents a discriminative model for the retrieval of pictures from text queries. The core idea of this approach is to minimize a loss directly related to the retrieval performance of the model. For that purpose, we rely on a ranking loss which ha ...
Exploratory search over a collection often requires users to iteratively apply a variety of strategies, such as searching for more general or more specific concepts in reaction to the information they encounter. Rich semantic models, such as WordNet, are p ...
Nowadays, network infrastructures are increasingly used in support to commercialization of digital multimedia content. Such kind of non-material goods, namely videos, music, still images and any other type of multi-media information are ready for the migra ...
We describe a user study evaluating two critiquing-based recommender agents based on three criteria: decision accuracy, decision effort, and user confidence. Results show that user-motivated critiques were more frequently applied and the example critiquing ...
American Association for Artificial Intelligence, Menlo Park, CA 94025-3496, United States2006