Geographic Information Retrieval (GIR): Searching Where and What.
Saved in:
| Title: | Geographic Information Retrieval (GIR): Searching Where and What. |
|---|---|
| Authors: | Larson, Ray R.1 ray@sherlock.berkeley.edu, Frontiera, Patricia2 pattyf@regis.berkeley.edu |
| Source: | SIGIR Forum. 2004 Special Edition, p600-600. 1p. |
| Subjects: | Geographic information systems, Information retrieval, Information storage & retrieval systems, QUERY (Information retrieval system), Algorithms, Search engines, Electronic information resource searching |
| Abstract: | This article reports on a demonstration of the Geographic Information Retrieval (GIR). The demonstration will show how explicit geospatial metadata and how inferred geographic information from texts can be exploited to provide effective and accurate ranked retrieval of geospatial information and relevant text documents using retrieval algorithms based on logistic regression with weighting coefficients estimated from a set of training data. A system that combines conventional probabilistic algorithms for text retrieval with algorithms for estimating probability of relevance for geographic spaces will be presented. Also to be demonstrated is the algorithm for GIR ranking that estimates probability of relevance based on a weighted set of parameters where the weights were derived using logistic regression from samples of a test collection. The demonstration will show: How graphical geospatial query specifications can be used to obtain sets of geospatial data ranked by probability of relevance; how different representations of the underlying data extents, including minimum bounding rectangles and convex hulls, compare to complex polygon representations in retrieval; how other characteristics, such as contextual geographic information, can be combined with knowledge of the query and candidate regions to improve retrieval effectiveness and how online gazetteer can be used to apply geographic retrieval to texts. The demonstrations will show real-time live searchers and geographic displays to illustrate the algorithms and methods described. |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
|---|---|
| Header | DbId: egs DbLabel: Engineering Source An: 15330597 AccessLevel: 6 PubType: Periodical PubTypeId: serialPeriodical PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Geographic Information Retrieval (GIR): Searching Where and What. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Larson%2C+Ray+R%2E%22">Larson, Ray R.</searchLink><relatesTo>1</relatesTo><i> ray@sherlock.berkeley.edu</i><br /><searchLink fieldCode="AR" term="%22Frontiera%2C+Patricia%22">Frontiera, Patricia</searchLink><relatesTo>2</relatesTo><i> pattyf@regis.berkeley.edu</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22SIGIR+Forum%22">SIGIR Forum</searchLink>. 2004 Special Edition, p600-600. 1p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Geographic+information+systems%22">Geographic information systems</searchLink><br /><searchLink fieldCode="DE" term="%22Information+retrieval%22">Information retrieval</searchLink><br /><searchLink fieldCode="DE" term="%22Information+storage+%26+retrieval+systems%22">Information storage & retrieval systems</searchLink><br /><searchLink fieldCode="DE" term="%22QUERY+%28Information+retrieval+system%29%22">QUERY (Information retrieval system)</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Search+engines%22">Search engines</searchLink><br /><searchLink fieldCode="DE" term="%22Electronic+information+resource+searching%22">Electronic information resource searching</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: This article reports on a demonstration of the Geographic Information Retrieval (GIR). The demonstration will show how explicit geospatial metadata and how inferred geographic information from texts can be exploited to provide effective and accurate ranked retrieval of geospatial information and relevant text documents using retrieval algorithms based on logistic regression with weighting coefficients estimated from a set of training data. A system that combines conventional probabilistic algorithms for text retrieval with algorithms for estimating probability of relevance for geographic spaces will be presented. Also to be demonstrated is the algorithm for GIR ranking that estimates probability of relevance based on a weighted set of parameters where the weights were derived using logistic regression from samples of a test collection. The demonstration will show: How graphical geospatial query specifications can be used to obtain sets of geospatial data ranked by probability of relevance; how different representations of the underlying data extents, including minimum bounding rectangles and convex hulls, compare to complex polygon representations in retrieval; how other characteristics, such as contextual geographic information, can be combined with knowledge of the query and candidate regions to improve retrieval effectiveness and how online gazetteer can be used to apply geographic retrieval to texts. The demonstrations will show real-time live searchers and geographic displays to illustrate the algorithms and methods described. |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=15330597 |
| RecordInfo | BibRecord: BibEntity: Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 1 StartPage: 600 Subjects: – SubjectFull: Geographic information systems Type: general – SubjectFull: Information retrieval Type: general – SubjectFull: Information storage & retrieval systems Type: general – SubjectFull: QUERY (Information retrieval system) Type: general – SubjectFull: Algorithms Type: general – SubjectFull: Search engines Type: general – SubjectFull: Electronic information resource searching Type: general Titles: – TitleFull: Geographic Information Retrieval (GIR): Searching Where and What. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Larson, Ray R. – PersonEntity: Name: NameFull: Frontiera, Patricia IsPartOfRelationships: – BibEntity: Dates: – D: 25 M: 07 Text: 2004 Special Edition Type: published Y: 2004 Identifiers: – Type: issn-print Value: 01635840 Titles: – TitleFull: SIGIR Forum Type: main |
| ResultId | 1 |
