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This work proposes a new approach to the retrieval of images from text queries. Contrasting with previous work, this method relies on a discriminative model: the parameters are selected in order to minimize a loss related to the ranking performance of the ...
The state-of-the-art techniques for processing multi-term queries in P2P environments are query flooding and inverted list intersection. However, it has been shown that due to scalability reasons both methods fail to support full-text search in large scale ...
The state-of-the-art techniques for processing multi-term queries in P2P environments are query flooding and inverted list intersection. However, it has been shown that due to scalability reasons both methods fail to support full-text search in large scale ...
Web search over peer-to-peer (P2P) networks shows promise to become an alternative to the state-of-the-art search engines since P2P overlays offer means for decentralized search across widely-distributed document collections. However, the design of effecti ...
Gnutella is still one of the most popular P2P systems with millions of users. The advantages of Gnutella are its low maintenance overhead, its excellent robustness properties, and its query processing flexibility. Recent improvements, such as the introduct ...
Assessing semantic similarity between text documents is a crucial aspect in Information Retrieval systems. In this work, we propose to use hyperlink information to derive a similarity measure that can then be applied to compare any text documents, with or ...
There has been an increasing research interest in developing full-text retrieval based on peer-to-peer (P2P) technology. So far, these research efforts have largely concentrated on efficiently distributing an index. However, ranking of the results retrieve ...
Text categorization is intrinsically a supervised learning task, which aims at relating a given text document to one or more predefined categories. Unfortunately, labeling such databases of documents is a painful task. We present in this paper a method tha ...
This work presents a neural network for the retrieval of images from text queries. The proposed network is composed of two main modules: the first one extracts a global picture representation from local block descriptors while the second one aims at solvin ...
This work presents a neural network for the retrieval of images from text queries. The proposed network is composed of two main modules: the first one extracts a global picture representation from local block descriptors while the second one aims at solvin ...
