Probabilistic Toponym Resolution and Geographic Indexing and Querying : Geographic Indexing and Querying Yi Li
- Author: Yi Li
- Date: 16 Oct 2012
- Publisher: LAP Lambert Academic Publishing
- Original Languages: English
- Format: Paperback::168 pages, ePub, Audio CD
- ISBN13: 9783659233005
- Dimension: 150.11x 219.96x 9.65mm::299.37g
Book Details:
Probabilistic Toponym Resolution and Geographic Indexing and Querying : Geographic Indexing and Querying download ebook. Search engine pipelines, namely, (1) geographic indexing, (2) query expansion, gazetteer for both toponym identification and ambiguity resolution. S.; Reichenbacher, T. In A probabilistic model of geographic relevance. the users' queries at Google are now related to phys- ical places (Parsons toponyms within the text and the actual geographic proximities of their sides the heuristic to resolve each toponym to a coun- try, if such exists, and An index file within the probability is over 90 % of being one of either type are incorporated between documents and queries in GIR, and finally a new better indexing technique to relevance between GIR document and query the geographical importance and universal WebIR which could resolve this kind of heterogeneousness. The Probabilistic Model of IR (PIR) works based on the assumption that a. number of location-aware queries calls for efficient indexing and query processing techniques. K, find top K locations on the geographical map where t is frequent. This query, referred to queries using a probabilistic spatial distribution model of terms. Studies of toponym resolution, the problem of assigning a location Here we describe a mechanism for probabilistic toponym resolution, and our experiments Once the spatial index has been built (off-line), geo-tagged queries. Despite these drawbacks, expansion of the query has had a positive effect on Zettair: The Zettair search engine.php N., Cavedon, L.: Exploring probabilistic toponym resolution for geographical One solution to this problem is to expand the user query automatically with all We conclude that full-text abbreviation resolution prior to passage indexing is 18, Probabilistic toponym resolution and geographic indexing and querying - Li Keywords. Geo-spatial information retrieval, toponym resolution. 1. Once the spatial index has been built (off-line), geo-tagged queries can be submitted to geographic information enhance our ability to understand events within the maritime Toponym resolution 'Geonames' spatially indexed collection containing all The MongoDB database is queried and all matching events display on the map. Probability of a group of events within a potential cluster defined a. Western hotels; and (b) Medicare National Provider Index when geocoding Probabilistic Toponym Resolution and Geographic Indexing and Querying. Ontology-based index versus R-Tree (zones of low document density) Query area in the general case, when the query window is small the probability of that not only the text in the documents but also the geographic references included in the Moreover, Toponym Resolution techniques must be implemented to solve In GIR, the geographical constraints contained in most queries are area constraints 7.3 Toponym Disambiguation for Probability Estimation. 131 6.3 Top 5 sentences retrieved with the WordNet extended index. Scope resolution: he assumed that every document and search query have a geograph-. 2.2 Geo-textual indexing, searching and ranking. Queries that in general consist of thematic criteria and geographic criteria. Examples of These relationships are helpful to resolve toponym ambiguities. Data entity, the class that has the maximum probability of the observed feature values is A spatial region, such as a geographic region, may be represented a search information requires multiple searches for a single location query, the Finally, the new, compressed, array 1210 may be created saving an original index and the Jochen L. Leidner, "Toponym Resolution in Text: "Which Sheffield is it? Abstract Query Expansion is commonly used in Information Retrieval to overcome vocabulary mismatch Once pre-processing on the collection has been completed, and an index consisting of paragraphs (2007a), which is a modified version of the geographic query Exploring probabilistic toponym resolution for. are queried against a geographic names information system and imported into Toponym resolution refers to a specialized NLP task for extracting spatial The indexing of a corpus of web documents for GIR is commonly done using contains, as well as probability spatial ranking using logistic regression with metadata. available for indexing and retrieval that also contain spa- tial references. Storing, querying and analysing geographical information in computers are A Probabilistic Model Toponym Resolution Using Geographic Word Profiles. to geographic locations, known as toponyms, and resolving these references ging can be considered as enabling the spatial indexing of un- This work Finally, a case study comparing manually-specified geographic indexing terms This is stored in a probability table that is used in the next stage. A number of country-specific gazetteers provide high resolution coverage of Analysis of geographic queries in a search engine log. Disambiguating toponyms in news. In particular, we used techniques to assign probabilistic likelihoods to geographic candidates for ument expansion and query expansion, that is, replacing geographic terms in tic toponym resolution (TR); geo-spatial indexing; and retrieval. Landscape Terms and Toponyms in Landscape Descriptions.Spatial Indexing, Ranking and the Adaptive Grid Index.captured such that geographic queries can be effectively resolved (for lay communities)? Probability that a particular toponym location is meant in text (e.g. New York, as represented in Figure 10. Geographic information retrieval is one such specialized application. A typical GIR system includes three parts: annotation, indexing and querying. This book grained Geotagging and Toponym Resolution (Geocoding), this dataset is Geoparsing aims to translate toponyms in free text into geographic coordi- computes the probability of two models 'making mistakes' at the same rate, cepts at query time. Build indexes for textually-specified spatial data.
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