Extracting People’s Names From RSS Feeds Using WordNet
Author(s)
K. Durant & M. Smith
Abstract
using WordNet
Department of Engineering and Applied Sciences
Abstract
Proper names are rich in content and it is essential we successfully identify them
to provide an accurate representation of the news. Identifying people’s names is
essential for article representation, representing the event of the story, identifying
the actors and receivers of action in the story, and for identifying the trends
happening within the news. Because of the importance names play, a name
extraction algorithm must be accurate and precise. It must also be efficient
because of the magnitude of the news corpora size and the timeliness of the data.
Typical name extraction systems uses supervised learning to identify names. We
take a different approach to name identification. We use WordNet to identify the
popular names within the corpora. The algorithm tracks the unidentified words
and uses standard templates to identify potential names within the unidentified
words. We also address the problem of names being common words found
within WordNet. We have created four gazetteers of words that may be a first
name, last name, title or suffix of a name. We use these lists along with the
surrounding text and simple templates to identify names. The algorithm can
simultaneously be performed when mapping the words to the terms within the
corpora. Our corpora are RSS news feeds, in particular the item element, which
is a semantic representation of a news article. We identify the names found
within the title and description elements of an RSS item. We exploit the fact that
the title element and the description element have the same topic for a news
article. Our algorithm has achieved a recall rate of 96% and a precision rate of
91%. We believe our approach performs well on this corpus because of the
simple vocabulary and succinct writing published in newspaper headlines and
lede statements.
Extracting people’s names from RSS feeds
Keywords: proper nouns, WordNet, RSS, gazetteer, template description.
Harvard University, USA
K. Durant & M. Smith
Keywords
proper nouns, WordNet, RSS, gazetteer, template description
Related Book
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