In the data privacy context, specifically, in statistical disclosure control techniques, microaggregation is a well-known microdata protection method, ensuring the confidentiality of each individual. In this paper, we propose a new approach of microaggregation to deal with semantic sets of categorical data, like text documents. This method relies on the WordNet framework that provides complete ...

In the data privacy context, specifically, in statistical disclosure control techniques, microaggregation is a well-known microdata protection method, ensuring the confidentiality of each individual. In this paper, we propose a new approach of microaggregation to deal with semantic sets of categorical data, like text documents. This method relies on the WordNet framework that provides complete ...

This paper proposes a new approach for keyword spotting, which is not based on HMMs. The proposed method employs a new discriminative learning procedure, in which the learning phase aims at maximizing the area under the ROC curve, as this quantity is the most common measure to evaluate keyword spotters. The keyword spotter we devise is based on nonlinearly mapping the input acoustic representat...

This paper proposes an efficient anti-keyword derivation method to improve the rejection performance of keyword spotting. In this method, each anti-keyword is derived from the large vocabulary lexicon considering acoustic similarity to keywords, making use of the confusion matrix. Experimental results show that a 3 % improvement of the rejection rate is obtained compared to conventional methods...

SUMMARY In this paper, a novel framework for extracting visual feature-based keyword relationships from an image database is proposed. From the characteristic that a set of relevant keywords tends to have common visual features, the keyword relationships in a target image database are extracted by using the following two steps. First, the relationship between each keyword and its corresponding ...

We introduce a method that extracts keywords in a language with the help of the other. In our approach, we bridge and fuse conventionally irrelevant word statistics in languages. The method involves estimating preferences for keywords w.r.t. domain topics and generating cross-lingual bridges for word statistics integration. At run-time, we transform parallel articles into word graphs, build cro...

There have been many domain-specific keyword extraction researches, but micro-blogoriented keyword extraction is just beginning. This paper researches into the keyword extraction from Chinese micro-blog. Taking the characteristics of micro-blog into account, such as short, topic divergence, etc., we propose a Chinese micro-blog keyword extraction method based on the combination of multi feature...

This paper describes a language model adaptation method for improving speech recognition of keywords in spoken queries occurring in information retrieval tasks. The method dynamically adapts language models to keyword categories within a single utterance; it first estimates keyword categories and their positions in an input query utterance and then dynamically changes the weights for language m...

Keyword queries are those terms that users enter and use to retrieve documents that have all or any of those terms. They are the most familiar and popular method used by ordinary users to search data. Keyword queries are highly ambiguous. Keyword search querying has emerged as one of the most effective way for information discovery, especially over HTML documents in the World Wide Web. Because ...