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Extracting entity profiles from semistructured information spaces
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| Zeitschriftentitel: | ACM SIGMOD Record |
|---|---|
| Personen und Körperschaften: | , |
| In: | ACM SIGMOD Record, 26, 1997, 4, S. 32-38 |
| Format: | E-Article |
| Sprache: | Englisch |
| veröffentlicht: |
Association for Computing Machinery (ACM)
|
| Schlagwörter: |
| author_facet |
Nado, Robert A. Huffman, Scott B. Nado, Robert A. Huffman, Scott B. |
|---|---|
| author |
Nado, Robert A. Huffman, Scott B. |
| spellingShingle |
Nado, Robert A. Huffman, Scott B. ACM SIGMOD Record Extracting entity profiles from semistructured information spaces Information Systems Software |
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nado, robert a. |
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Nado, Robert A. Huffman, Scott B. 0163-5808 Association for Computing Machinery (ACM) Information Systems Software http://dx.doi.org/10.1145/271074.271083 <jats:p> A semistructured information space consists of multiple collections of textual documents containing fielded or tagged sections. The space can be highly heterogeneous, because each collection has its own schema, and there are no enforced keys or formats for data items across collections. Thus, structured methods like SQL cannot be easily employed, and users often must make do with only full-text search. In this paper, we describe an approach that provides structured querying for particular types of <jats:italic>entities</jats:italic> , such as companies and people. Entity-based retrieval is enabled by <jats:italic>normalizing</jats:italic> entity references in a heuristic, type-dependent manner. The approach can be used to retrieve documents and can also be used to construct entity profiles — summaries of commonly sought information about an entity based on the documents' content. The approach requires only a modest amount of meta-information about the source collections, much of which is derived automatically. </jats:p> Extracting entity profiles from semistructured information spaces ACM SIGMOD Record |
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| title |
Extracting entity profiles from semistructured information spaces |
| title_unstemmed |
Extracting entity profiles from semistructured information spaces |
| title_full |
Extracting entity profiles from semistructured information spaces |
| title_fullStr |
Extracting entity profiles from semistructured information spaces |
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Extracting entity profiles from semistructured information spaces |
| title_short |
Extracting entity profiles from semistructured information spaces |
| title_sort |
extracting entity profiles from semistructured information spaces |
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Information Systems Software |
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http://dx.doi.org/10.1145/271074.271083 |
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1997 |
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32-38 |
| description |
<jats:p>
A semistructured information space consists of multiple collections of textual documents containing fielded or tagged sections. The space can be highly heterogeneous, because each collection has its own schema, and there are no enforced keys or formats for data items across collections. Thus, structured methods like SQL cannot be easily employed, and users often must make do with only full-text search. In this paper, we describe an approach that provides structured querying for particular types of
<jats:italic>entities</jats:italic>
, such as companies and people. Entity-based retrieval is enabled by
<jats:italic>normalizing</jats:italic>
entity references in a heuristic, type-dependent manner. The approach can be used to retrieve documents and can also be used to construct entity profiles — summaries of commonly sought information about an entity based on the documents' content. The approach requires only a modest amount of meta-information about the source collections, much of which is derived automatically.
</jats:p> |
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| description | <jats:p> A semistructured information space consists of multiple collections of textual documents containing fielded or tagged sections. The space can be highly heterogeneous, because each collection has its own schema, and there are no enforced keys or formats for data items across collections. Thus, structured methods like SQL cannot be easily employed, and users often must make do with only full-text search. In this paper, we describe an approach that provides structured querying for particular types of <jats:italic>entities</jats:italic> , such as companies and people. Entity-based retrieval is enabled by <jats:italic>normalizing</jats:italic> entity references in a heuristic, type-dependent manner. The approach can be used to retrieve documents and can also be used to construct entity profiles — summaries of commonly sought information about an entity based on the documents' content. The approach requires only a modest amount of meta-information about the source collections, much of which is derived automatically. </jats:p> |
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| spelling | Nado, Robert A. Huffman, Scott B. 0163-5808 Association for Computing Machinery (ACM) Information Systems Software http://dx.doi.org/10.1145/271074.271083 <jats:p> A semistructured information space consists of multiple collections of textual documents containing fielded or tagged sections. The space can be highly heterogeneous, because each collection has its own schema, and there are no enforced keys or formats for data items across collections. Thus, structured methods like SQL cannot be easily employed, and users often must make do with only full-text search. In this paper, we describe an approach that provides structured querying for particular types of <jats:italic>entities</jats:italic> , such as companies and people. Entity-based retrieval is enabled by <jats:italic>normalizing</jats:italic> entity references in a heuristic, type-dependent manner. The approach can be used to retrieve documents and can also be used to construct entity profiles — summaries of commonly sought information about an entity based on the documents' content. The approach requires only a modest amount of meta-information about the source collections, much of which is derived automatically. </jats:p> Extracting entity profiles from semistructured information spaces ACM SIGMOD Record |
| spellingShingle | Nado, Robert A., Huffman, Scott B., ACM SIGMOD Record, Extracting entity profiles from semistructured information spaces, Information Systems, Software |
| title | Extracting entity profiles from semistructured information spaces |
| title_full | Extracting entity profiles from semistructured information spaces |
| title_fullStr | Extracting entity profiles from semistructured information spaces |
| title_full_unstemmed | Extracting entity profiles from semistructured information spaces |
| title_short | Extracting entity profiles from semistructured information spaces |
| title_sort | extracting entity profiles from semistructured information spaces |
| title_unstemmed | Extracting entity profiles from semistructured information spaces |
| topic | Information Systems, Software |
| url | http://dx.doi.org/10.1145/271074.271083 |