in the document - XP
... organization. Both incoming and internally generated documents are automatically abstracted, characterized by a word pattern, and sent automatically to appropriate action points.” ...
... organization. Both incoming and internally generated documents are automatically abstracted, characterized by a word pattern, and sent automatically to appropriate action points.” ...
A New Entity Salience Task with Millions of Training Examples
... tagger and dependency parser, comparable in accuracy to the current Stanford dependency parser (Klein and Manning, 2003); an NP extractor that uses POS tags and dependency edges to identify a set of entity mentions; a coreference resolver, comparable to that of Haghighi and Klein, (2009) for cluster ...
... tagger and dependency parser, comparable in accuracy to the current Stanford dependency parser (Klein and Manning, 2003); an NP extractor that uses POS tags and dependency edges to identify a set of entity mentions; a coreference resolver, comparable to that of Haghighi and Klein, (2009) for cluster ...
Update Summarization - NUS School of Computing
... – Cue/stigma phrases – Sentence position (relative to document, section, paragraph) – Sentence length – TF×IDF, TF scores – Similarity (with title, context, query) ...
... – Cue/stigma phrases – Sentence position (relative to document, section, paragraph) – Sentence length – TF×IDF, TF scores – Similarity (with title, context, query) ...
NUS at DUC 2007 - National University of Singapore
... – Models how nodes in multi-document graphs are added – Skew degree = how many iterations to wait before adding the 1st sentence of the next document ...
... – Models how nodes in multi-document graphs are added – Skew degree = how many iterations to wait before adding the 1st sentence of the next document ...
Can Word Probabilities from LDA be Simply Added up to Represent
... This research was supported by the National Science Foundation (DRK-12-0918409, 1108845), the Institute of Education Sciences (R305H050169, R305B070349, R305A080589, R305A080594, R305G020018, R305C120001), Army Research Lab (W911INF12-2-0030), and the Office of Naval Research (N00014-00-1-0600, N000 ...
... This research was supported by the National Science Foundation (DRK-12-0918409, 1108845), the Institute of Education Sciences (R305H050169, R305B070349, R305A080589, R305A080594, R305G020018, R305C120001), Army Research Lab (W911INF12-2-0030), and the Office of Naval Research (N00014-00-1-0600, N000 ...
Multi-Sentence Compression: Finding Shortest Paths
... of news classification and clustering with a production quality. Apart from that, it is a rich source of multilingual data. We collected news clusters in English and Spanish, 10-30 articles each, 24 articles on average. To get sets of similar sentences we aggregated first sentences from every articl ...
... of news classification and clustering with a production quality. Apart from that, it is a rich source of multilingual data. We collected news clusters in English and Spanish, 10-30 articles each, 24 articles on average. To get sets of similar sentences we aggregated first sentences from every articl ...
Descriptive Data Summarization
... Trimmed mean – A major problem with the mean is its sensitivity to extreme (e.g., outlier) values. – Even a small number of extreme values can corrupt the mean. – the trimmed mean is the mean obtained after cutting off values at the high and low extremes. – For example, we can sort the values and re ...
... Trimmed mean – A major problem with the mean is its sensitivity to extreme (e.g., outlier) values. – Even a small number of extreme values can corrupt the mean. – the trimmed mean is the mean obtained after cutting off values at the high and low extremes. – For example, we can sort the values and re ...
CL35491494
... thus leading to better results in shorter time. Keyphrases are representative of the complete document. Irrelevant results can be reduced if search is based on keyphrases. ...
... thus leading to better results in shorter time. Keyphrases are representative of the complete document. Irrelevant results can be reduced if search is based on keyphrases. ...
Machine Reading
... Machine Reading (MR) is very different from current semantic NLP research areas such as Information Extraction (IE) or Question Answering (QA). Many NLP tasks utilize supervised learning techniques, which rely on hand-tagged training examples. For example, IE systems often utilize extraction rules l ...
... Machine Reading (MR) is very different from current semantic NLP research areas such as Information Extraction (IE) or Question Answering (QA). Many NLP tasks utilize supervised learning techniques, which rely on hand-tagged training examples. For example, IE systems often utilize extraction rules l ...
Extracting Attractive Summaries for News Propagation on Microblogs
... concerned by a large number of people. The common way of releasing news on microblogs is to post human-edited short summaries on microblog sites, and the corresponding full news articles can be found via a URL link to external news portals. Usually, an attractive news summary will often bring more p ...
... concerned by a large number of people. The common way of releasing news on microblogs is to post human-edited short summaries on microblog sites, and the corresponding full news articles can be found via a URL link to external news portals. Usually, an attractive news summary will often bring more p ...
A Topic-driven Summarization using K-mean
... query-focused multi-document summarization that uses k-mean clustering, term-frequency and inversesentence- frequency method for sentence weighting to rank the sentences of the documents with respect to a given query. The proposed method finds the proximity of documents and query, and later uses thi ...
... query-focused multi-document summarization that uses k-mean clustering, term-frequency and inversesentence- frequency method for sentence weighting to rank the sentences of the documents with respect to a given query. The proposed method finds the proximity of documents and query, and later uses thi ...