Name Recognition and Retrieval Performance

Thompson, Paul; Dozier, Christopher

doi:10.1007/978-94-017-2388-6_10

Cited by 7 publications

(5 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Name recognition and matching has long been a focus in IE and IR research, and sophisticated methods have been developed, see (Thompson & Dozier 1999) for a study in the legal domain. These methods go beyond what is needed for SMILE, where the names are usually given in the opinion header.…”

Section: A-z][a-z]* [A-z][a-z]*-[a-z][a-z]* $Organizationmentioning

confidence: 99%

Improving the representation of legal case texts with information extraction methods

Brüninghaus

Ashley

2001

Proceedings of the 8th International Conference on Artificial Intelligence and Law

View full text Add to dashboard Cite

The prohibitive cost of assigning indices to textual cases is a major obstacle for the practical use of AI and Law systems supporting reasoning and arguing with cases. While progress has been made toward extracting certain facts from well-structured case texts or classifying case abstracts under Key Number concepts, these methods still do not suffice for the complexity of indexing concepts in CBR systems.In this paper, we lay out how a better example representation may facilitate classification-based indexing. Our hypotheses are that (1) abstracting from the individual actors and events in cases, (2) capturing actions in multi-word features, and (3) recognizing negation, can lead to a better representation of legal case texts for automatic indexing. We discuss how to implement these techniques with state-of-the-art NLP tools. Preliminary experimental results suggest that a combination of domain-specific knowledge and information extraction techniques can be used to generalize from the examples and derive more powerful features.

show abstract

Section: A-z][a-z]* [A-z][a-z]*-[a-z][a-z]* $Organizationmentioning

confidence: 99%

Improving the representation of legal case texts with information extraction methods

Brüninghaus

Ashley

2001

Proceedings of the 8th International Conference on Artificial Intelligence and Law

View full text Add to dashboard Cite

show abstract

“…Preliminary research suggests that recognizing named entities in data and queries may lead to a significant improvement in retrieval quality (Thompson & Dozier, 1999). Such an approach may complement Entity Indexing, but it does not yet meet the controlled vocabulary indexing and accuracy requirements for Entity Indexing.…”

Section: Related Workmentioning

confidence: 99%

Large-scale controlled vocabulary indexing for named entities

Wasson¹

2000

Proceedings of the Sixth Conference on Applied Natural Language Processing -

View full text Add to dashboard Cite

show abstract

“…A PN variant can be described as a text occurrence that is conceptually well related with the correct form, or canonical form, of a name. The recognition of the variant of these sequences would revolve around one of three procedures specified by Thompson and Dozier (1999): name-recognition, name-matching, and name-searching.…”

Section: Introductionmentioning

confidence: 99%

Approximate personal name‐matching through finite‐state graphs

Gálvez

Anegón

2007

J. Am. Soc. Inf. Sci.

View full text Add to dashboard Cite

This article shows how finite-state methods can be employed in a new and different task: the conflation of personal name variants in standard forms. In bibliographic databases and citation index systems, variant forms create problems of inaccuracy that affect information retrieval, the quality of information from databases, and the citation statistics used for the evaluation of scientists' work. A number of approximate string matching techniques have been developed to validate variant forms, based on similarity and equivalence relations. We classify the personal name variants as nonvalid and valid forms. In establishing an equivalence relation between valid variants and the standard form of its equivalence class, we defend the application of finite-state transducers. The process of variant identification requires the elaboration of: (a) binary matrices and (b) finite-state graphs. This procedure was tested on samples of author names from bibliographic records, selected from the Library and Information Science Abstracts and Science Citation Index Expanded databases. The evaluation involved calculating the measures of precision and recall, based on completeness and accuracy. The results demonstrate the usefulness of this approach, although it should be complemented with methods based on similarity relations for the recognition of spelling variants and misspellings.

show abstract

Name Recognition and Retrieval Performance

Cited by 7 publications

References 5 publications

Improving the representation of legal case texts with information extraction methods

Improving the representation of legal case texts with information extraction methods

Large-scale controlled vocabulary indexing for named entities

Approximate personal name‐matching through finite‐state graphs

Contact Info

Product

Resources

About