By Christian Sallaberry
This e-book addresses the sphere of geographic details extraction and retrieval from textual records. Geographic details retrieval is a quickly rising topic, a pattern fostered by means of the becoming energy of the net and the rising probabilities of info dissemination. After positioning his paintings during this box in bankruptcy 1, the writer makes proposals within the following chapters. bankruptcy 2 makes a speciality of spatial and temporal details indexing and retrieval in corpora of textual files. Propositions for either spatial and temporal info retrieval (IR) are made. Read more...
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Additional resources for Geographical information retrieval in textual corpora
Taken from the book Voyages aux Pyrénées – Pimientos editions, describes two places: (1) the surroundings of Pau whose place of reference is Pau and (2) the zone between Assat and Eaux-Chaudes whose two places of reference are Assat and Eaux-Chaudes. The indicators used here are the indicators of adjacency. 26 Geographical Information Retrieval in Textual Corpora To annotate the information as we have seen in the previous sections, it ﬁrst has to be identiﬁed in the texts and interpreted during the extraction phase.
3 presents propositions found in published literature dealing with the problem of space and time in the processes of annotation and indexing of texts as well as in those of IR. 4 describes our propositions for indexing together with the spatial and temporal IR. 5. 2. Review of challenges, hypotheses and research objectives Here, we review a subset of issues, hypotheses and research objectives described in Chapter 1. The main issue dealt with in this chapter is thus expressed in the following question: What models of representation and retrieval of spatial and temporal information should be proposed for the access by geographic content to textual corpora?
A NE detector generally uses a machine learning or an ad hoc rule-base approach to detect and categorize NEs [POI 03]. The learning-based NER is done from texts manually labeled by experts: statistical analysis methods (the texts are considered to be a stream of characters) allow the construction of generic patterns that can be used on a bigger corpus. The ad hoc approach is based on lexical patterns constructed manually with the help of experts: “a proper noun preceded by the preposition at, is potentially a place” is an example of such a pattern.