NDLI: Semantically enhanced matchmaking of consumers and providers: a Canadian real estate case study

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Semantically enhanced matchmaking of consumers and providers: a Canadian real estate case study

Content Provider	ACM Digital Library
Author	Alhajj, Reda Triant, Flouris Shafiq, Omair Poon, Freddy Chen, Alan Chin, Thomas Rokne, Jon Bentrovato, Matt
Abstract	Matchmaking services connecting consumers and providers on the internet have become phenomenally important in today's world. Whereas the matchmaking was by traditional media such as print and television in the past it is now expected to include the internet. Consumers expect these services to be readily available as this can only be accomplished via the internet Providers that do not have an internet presence are therefore severely disadvantage in the competition for customers (consumers). The decline of the traditional physical music store and the ascendancy of the virtual iTunes store is a perfect example of this. As the traditional stores go bankrupt and go out of business has also become the largest music retailer in the United States of America. Consumers simply do not want to spend extra energy to get what they want. If the music can be purchased and downloaded from the comfort of their own home, the consumers (customers) will do just that. Therefore online matchmaking services are a hot topic of discussion for many companies, as they are finding ways to provide the fastest, cheapest and most efficient methods for consumers to easily access their services. This paper suggests the use of semantic technology to create and query a database, specifically a database for matchmaking for consumers and providers in a real estate scenario. While traditional databases based on Entity Relational Schemas are the de facto standard presently on the database scene, it itself has limitations that Semantic technology can overcome. The Semantic database makes use of complex description logic reasoners, such as Fact++ and pellet, coupled with rich conceptual schemas known as Ontologies. This allows for much more powerful and expressive queries than that of traditional database query languages such as SQL and relational algebra.
Starting Page	198
Ending Page	205
Page Count	8
File Format	PDF
ISBN	9781450307840
DOI	10.1145/2095536.2095570
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2011-12-05
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Semantic queries Ontologies Real estate Semantic rules
Content Type	Text
Resource Type	Article

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