Ex: When viewing http://www.bibsonomy.org/user/schmitz/linux, you will be offered the possibility of seeing the tag linux as a concept. That way, you will also see those resources not tagged with linux themselves, but with a direct subtag thereof, for exa
Report from the 13th ACM Conference on Information and Knowledge Management, Washington DC, USA, 2004. Sponsors: ACM Special Interest Group on Information Retrieval, ACM Association for Computing Machinery
Data mining (DM), also called Knowledge-Discovery in Databases (KDD) or Knowledge-Discovery and Data Mining, is the process of automatically searching large volumes of data for patterns using tools such as classification, association rule mining, clusteri
Data mining (DM), also called Knowledge-Discovery in Databases (KDD) or Knowledge-Discovery and Data Mining, is the process of automatically searching large volumes of data for patterns using tools such as classification, association rule mining, clusteri
It is important to differentiate between text data mining and information access (or information retrieval, as it is more widely known)... the goal of data mining is to discover or derive new information from data, finding patterns across datasets, and/o
It is important to differentiate between text data mining and information access (or information retrieval, as it is more widely known)... the goal of data mining is to discover or derive new information from data, finding patterns across datasets, and/o
Ever notice that before you can really do a good web search, you have to actually know something about your search topic? Let's say you want to learn more about jazz. But you don't know any of the "keywords," the musicians, the composers, the talent. S
Ever notice that before you can really do a good web search, you have to actually know something about your search topic? Let's say you want to learn more about jazz. But you don't know any of the "keywords," the musicians, the composers, the talent. S
Lexical ambiguity is a fundamental problem in Information Retrieval (IR), especially in the medical domain. Many systems use a subset of the words contained in the document to represent the content, but they are faced with the problem of ambiguity.
Lexical ambiguity is a fundamental problem in Information Retrieval (IR), especially in the medical domain. Many systems use a subset of the words contained in the document to represent the content, but they are faced with the problem of ambiguity.
It might seem redundant to have semantic tagging when you can basically find anything you can think of with simple searches in Google or Yahoo. But del.icio.us seems to be most surprising when you're trying to find things that relate to what you're intere
It might seem redundant to have semantic tagging when you can basically find anything you can think of with simple searches in Google or Yahoo. But del.icio.us seems to be most surprising when you're trying to find things that relate to what you're intere
Category search within digital repositories is poorly supported. This means that people wishing to access the assets of digital repositories are largely limited to keyword search, which means they must know what they want in order to look for it. Our part
Category search within digital repositories is poorly supported. This means that people wishing to access the assets of digital repositories are largely limited to keyword search, which means they must know what they want in order to look for it. Our part
This discussion of XML and semantics kicks off a column by Uche Ogbuji on knowledge management aspects of XML, including metadata, semantics, Resource Description Framework (RDF), Topic Maps, and autonomous agents. Approaching the topic from a practical p
This discussion of XML and semantics kicks off a column by Uche Ogbuji on knowledge management aspects of XML, including metadata, semantics, Resource Description Framework (RDF), Topic Maps, and autonomous agents. Approaching the topic from a practical p