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By Tutut Herawan, Iwan Tri Riyadi Yanto, Mustafa Mat Deris (auth.), Ngoc Thanh Nguyen, Radosław Katarzyniak, Shyi-Ming Chen (eds.)
The e-book involves 32 prolonged chapters that have been in line with chosen submissions to the poster consultation prepared in the course of the second Asian convention on clever info and Database platforms (24-26 March 2010 in Hue, Vietnam). The booklet is equipped into 4 elements dedicated to info retrieval and administration, carrier composition and user-centered strategy, facts mining and data extraction, and computational intelligence, respectively. All chapters within the ebook talk about theoretical and sensible matters with regards to integration of man-made intelligence and database applied sciences with a view to boost new periods of clever info structures. Such mixture of synthetic intelligence and database applied sciences is a quick turning out to be subfield of contemporary computing device technology, vital as a result of consistent improvement of networked info platforms. New international multimedia platforms utilized by heterogeneous populations demand those advancements. The editors desire that the booklet could be valuable for graduate and PhD scholars of computing device technological know-how, in addition to for mature teachers, researchers and practitioners drawn to powerful program of synthetic intelligence and database structures to fashionable details environments. it's the desire of the editors that readers of this quantity can locate many inspiring principles and influential sensible examples and use them of their destiny work.
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Additional info for Advances in intelligent information and database systems
Therefore the correctness of the facts is about 95%. In addition, with logical extraction techniques and a flexible architecture, YAGO can be further extended in future. Note that, to have more relation types and facts, we can employ and combine it with some other ontologies. 2 Query Expansion Figure 2 shows the main steps of our method to determine latently related entities for a query: Ontology-Based Query Expansion with Latently Related Named Entities Recognizing Relation Phrases Determining Relations Recognizing Entities 47 Determining Related Entities Fig.
Com/kim/ Ontology-Based Query Expansion with Latently Related Named Entities 45 Table 1. Mapping interrogative words to entity types Interrogative Word Who Which Where What NE Class Example Query Person Who was the first American in space? Woman Who was the lead actress in the movie "Sleepless in Seattle"? S.? City Which city has the oldest relationship as a sister-city with Los Angeles? Location Where did Dylan Thomas die? WaterRegion Where is it planned to berth the merchant ship, Lane Victory, which Merchant Marine veterans are converting into a floating museum?
H. Cao Current search engines like Yahoo and Google mainly use keywords to search for documents. Much semantic information of documents or user's queries is lost when they are represented by only ‘bags of words’. Meanwhile, people often use named entities (NE) in information search. Specifically, in the top 10 search terms by YahooSearch1 and GoogleSearch2 in 2008, there are respectively 10 and 9 ones that are NEs. Named entities are those that are referred to by names such as people, organizations, and locations () and could be described in ontologies.