Arrow Research search

Author name cluster

Ozlem Uzuner

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

3 papers
1 author row

Possible papers

3

AAAI Conference 2005 Conference Paper

Capturing Expression Using Linguistic Information

  • Ozlem Uzuner

Recognizing similarities between literary works for copyright infringement detection requires evaluating similarity in the expression of content. Copyright law protects expression of content; similarities in content alone are not enough to indicate infringement. Expression refers to the way people convey particular information; it captures both the information and the manner of its presentation. In this paper, we present a novel set of linguistically informed features that provide a computational definition of expression and that enable accurate recognition of individual titles and their paraphrases more than 80% of the time. In comparison, baseline features, e. g. , tfidf-weighted keywords, function words, etc. , give an accuracy of at most 53%. Our computational definition of expression uses linguistic features that are extracted from POS-tagged text using context-free grammars, without incurring the computational cost of full parsers. The results indicate that informative linguistic features do not have to be computationally prohibitively expensive to extract.

AAAI Conference 1999 Short Paper

Word Sense Disambiguation for Information Retrieval

  • Ozlem Uzuner
  • Boris Katz
  • Deniz Yuret
  • MIT Artificial Intelligence Laboratory

Despite their increasing importance as data retrieval tools, most Information Retrieval (IR) systems are deficient in precision and recall. Lack of disambiguation power is one reason for the poor performance of these systems. Correctly disambiguating and expanding a query with intended synonyms before retrieval may improve the performance. We use the local context of a word to identify its sense. In our case, the local context of a word is the ordered list of words from the closest content word on each side of the target word up to the target word which is expressed as a placeholder.