We demonstrate the application of Nuisance Attribute Projection (NAP), Within-Class Covariance Normalization (WCCN), a new standard kernel, and keyword weighting for the keywordbased HMM supervector speaker recognition system. On our development set (SRE04 8-side training), we achieve 22.6% and 16.2% EER improvements using NAP and WCCN respectively, a 19.5% EER improvement using NAP and WCCN jo...

Multimedia databases contain an increasing amount of videos that are hardly semantically accessed. Among the useful indices that can be extracted from the sound track, the presence of a keyword at some place plays a prominent role. This paper deals with the specificities of such a keyword spotter and the enhancement brought to our previous technique, [1] based on frame labeling. To be useful, s...

Keyword search is a user-friendly mechanism for retrieving XML data in web and scientific applications. An intuitively compelling but vaguely defined goal is to identify matches to query keywords that are relevant to the user. However, it is hard to directly evaluate the relevance of query results due to the inherent ambiguity of search semantics. In this work, we investigate an axiomatic frame...

With the development of cloud computing, the sensitive information of outsourced data is at risk of unauthorized accesses. To protect data privacy, the sensitive data should be encrypted by the data owner before outsourcing, which makes the traditional and efficient plaintext keyword search technique useless. Hence, it is an especially important thing to explore secure encrypted cloud data sear...

Keyword search is a user-friendly mechanism for retrieving XML data in web and scientific applications. An intuitively compelling but vaguely defined goal is to identify matches to query keywords that are relevant to the user. However, it is hard to directly evaluate the relevance of query results due to the inherent ambiguity of search semantics. In this work, we investigate an axiomatic frame...

Most question answering systems narrow down their search space by issuing a boolean IR query on a keyword indexed corpus. This technique often proves futile for definitional questions, because they only contain one keyword or name. Thus, an IR search for only that term is likely to produce many spurious results; documents that contain mentions of the keyword, but not in a definitional context. ...

We study the problem of context-sensitive ranking for document retrieval, where a context is defined as a sub-collection of documents, and is specified by queries provided by domain-interested users. The motivation of context-sensitive search is that the ranking of the same keyword query generally depends significantly on the context. The underlying reason is that the underlying keyword statist...

Multimedia databases contain an increasing amount of videos that are hardly semantically accessed. Among the useful indices that can be extracted from the sound track, the presence of a keyword at some place plays a prominent role. This paper deals with the specificities of such a keyword spotter and the enhancement brought to our previous technique, [1] based on frame labeling. To be useful, s...

Several approaches have been proposed for near real-time detection and prediction of the spread of influenza. These include search query data for influenza-related terms, which has been explored as a tool for augmenting traditional surveillance methods. In this paper, we present a method that uses Internet search query data from Baidu to model and monitor influenza activity in China. The object...

In many collaborative systems, researchers are interested in creating representative user profiles. In this paper, we are particularly interested in using social labeling and automatic keyword extraction techniques for generating user profiles. Social labeling is a process in which users manually tag other users with keywords. Automatic keyword extraction is a technique that selects the most sa...