Previous research in novelty detection has focused on the task of finding novel material, given a set or stream of documents on a certain topic. This study investigates the more difficult two-part task defined by the TREC 2002 novelty track: given a topic and a group of documents relevant to that topic, 1) find the relevant sentences from the documents, and 2) find the novel sentences from the collection of relevant sentences. Our research shows that the former step appears to be the more difficult part of this task, and that the performance of novelty measures is very sensitive to the presence of non-relevant sentences
Automated mining of novel documents or sentences from chronologically ordered documents or sentences...
For the TREC 2004 Novelty track, UMass participated in all four tasks. Although finding relevant sen...
Novelty detection is a difficult task, particularly at sentence level. Most of the approaches propos...
The detection of new information in a document stream is an important component of many potential ap...
The detection of new information in a document stream is an important component of many potential ap...
The detection of new information in a document stream is an important component of many potential ap...
We demonstrate the value of using context in a new-information detection system that achieved the hi...
The automatic detection of novelty, or newness, as part of an information retrieval system would gre...
Methods for detecting sentences in an input document set, which are both relevant and novel with res...
In this paper, a new novelty detection approach based on the identification of sentence level inform...
In the novelty task on sentence level, the amount of information used in similarity computation is t...
The novelty track was first introduced in TREC 2002. Given a TREC topic and an ordered list of docum...
This paper explores a combination of machine learning, approximate text segmentation and a vector-sp...
In TREC 2004, IRIT modified important features of t he strategy that was developed for TREC 2003. Ch...
Novelty detection system is used to extract documents with new or novel information from list of doc...
Automated mining of novel documents or sentences from chronologically ordered documents or sentences...
For the TREC 2004 Novelty track, UMass participated in all four tasks. Although finding relevant sen...
Novelty detection is a difficult task, particularly at sentence level. Most of the approaches propos...
The detection of new information in a document stream is an important component of many potential ap...
The detection of new information in a document stream is an important component of many potential ap...
The detection of new information in a document stream is an important component of many potential ap...
We demonstrate the value of using context in a new-information detection system that achieved the hi...
The automatic detection of novelty, or newness, as part of an information retrieval system would gre...
Methods for detecting sentences in an input document set, which are both relevant and novel with res...
In this paper, a new novelty detection approach based on the identification of sentence level inform...
In the novelty task on sentence level, the amount of information used in similarity computation is t...
The novelty track was first introduced in TREC 2002. Given a TREC topic and an ordered list of docum...
This paper explores a combination of machine learning, approximate text segmentation and a vector-sp...
In TREC 2004, IRIT modified important features of t he strategy that was developed for TREC 2003. Ch...
Novelty detection system is used to extract documents with new or novel information from list of doc...
Automated mining of novel documents or sentences from chronologically ordered documents or sentences...
For the TREC 2004 Novelty track, UMass participated in all four tasks. Although finding relevant sen...
Novelty detection is a difficult task, particularly at sentence level. Most of the approaches propos...