-
Frederichs, A.: Natürlichsprachige Abfrage und 3-D-Visualisierung von Wissenszusammenhängen (2007)
0.00
0.0037468998 = product of:
0.026228298 = sum of:
0.0050448296 = weight(_text_:information in 566) [ClassicSimilarity], result of:
0.0050448296 = score(doc=566,freq=2.0), product of:
0.052020688 = queryWeight, product of:
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.029633347 = queryNorm
0.09697737 = fieldWeight in 566, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.0390625 = fieldNorm(doc=566)
0.021183468 = weight(_text_:retrieval in 566) [ClassicSimilarity], result of:
0.021183468 = score(doc=566,freq=4.0), product of:
0.08963835 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.029633347 = queryNorm
0.23632148 = fieldWeight in 566, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.0390625 = fieldNorm(doc=566)
0.14285715 = coord(2/14)
- Abstract
- Eine der größten Herausforderungen für alle technischen Anwendungen ist die sogenannte Mensch-Maschine-Schnittstelle, also der Problemkreis, wie der bedienende Mensch mit der zu bedienenden Technik kommunizieren kann. Waren die Benutzungsschnittstellen bis Ende der Achtziger Jahre vor allem durch die Notwendigkeit des Benutzers geprägt, sich an die Erfordernisse der Maschine anzupassen, so wurde mit Durchsetzung grafischer Benutzungsoberflächen zunehmend versucht, die Bedienbarkeit so zu gestalten, dass ein Mensch auch ohne größere Einarbeitung in die Lage versetzt werden sollte, seine Befehle der Technik - letztlich also dem Computer - zu übermitteln. Trotz aller Fortschritte auf diesem Gebiet blieb immer die Anforderung, der Mensch solle auf die ihm natürlichste Art und Weise kommunizieren können, mit menschlicher Sprache. Diese Anforderung gilt gerade auch für das Retrieval von Informationen: Warum ist es nötig, die Nutzung von Booleschen Operatoren zu erlernen, nur um eine Suchanfrage stellen zu können? Ein anderes Thema ist die Frage nach der Visualisierung von Wissenszusammenhängen, die sich der Herausforderung stellt, in einem geradezu uferlos sich ausweitenden Informationsangebot weiterhin den Überblick behalten und relevante Informationen schnellstmöglich finden zu können.
- Source
- Wa(h)re Information: 29. Österreichischer Bibliothekartag Bregenz, 19.-23.9.2006. Hrsg.: Harald Weigel
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Niemi, T.; Jämsen , J.: ¬A query language for discovering semantic associations, part I : approach and formal definition of query primitives (2007)
0.00
0.0035812336 = product of:
0.025068633 = sum of:
0.010089659 = weight(_text_:information in 591) [ClassicSimilarity], result of:
0.010089659 = score(doc=591,freq=8.0), product of:
0.052020688 = queryWeight, product of:
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.029633347 = queryNorm
0.19395474 = fieldWeight in 591, product of:
2.828427 = tf(freq=8.0), with freq of:
8.0 = termFreq=8.0
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.0390625 = fieldNorm(doc=591)
0.014978974 = weight(_text_:retrieval in 591) [ClassicSimilarity], result of:
0.014978974 = score(doc=591,freq=2.0), product of:
0.08963835 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.029633347 = queryNorm
0.16710453 = fieldWeight in 591, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.0390625 = fieldNorm(doc=591)
0.14285715 = coord(2/14)
- Abstract
- In contemporary query languages, the user is responsible for navigation among semantically related data. Because of the huge amount of data and the complex structural relationships among data in modern applications, it is unrealistic to suppose that the user could know completely the content and structure of the available information. There are several query languages whose purpose is to facilitate navigation in unknown structures of databases. However, the background assumption of these languages is that the user knows how data are related to each other semantically in the structure at hand. So far only little attention has been paid to how unknown semantic associations among available data can be discovered. We address this problem in this article. A semantic association between two entities can be constructed if a sequence of relationships expressed explicitly in a database can be found that connects these entities to each other. This sequence may contain several other entities through which the original entities are connected to each other indirectly. We introduce an expressive and declarative query language for discovering semantic associations. Our query language is able, for example, to discover semantic associations between entities for which only some of the characteristics are known. Further, it integrates the manipulation of semantic associations with the manipulation of documents that may contain information on entities in semantic associations.
- Content
- Part II: Journal of the American Society for Information Science and Technology. 58(2007) no.11, S.1686-1700.
- Source
- Journal of the American Society for Information Science and Technology. 58(2007) no.11, S.1559-1568
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Niemi, T.; Jämsen, J.: ¬A query language for discovering semantic associations, part II : sample queries and query evaluation (2007)
0.00
0.0033881254 = product of:
0.023716876 = sum of:
0.008737902 = weight(_text_:information in 580) [ClassicSimilarity], result of:
0.008737902 = score(doc=580,freq=6.0), product of:
0.052020688 = queryWeight, product of:
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.029633347 = queryNorm
0.16796975 = fieldWeight in 580, product of:
2.4494898 = tf(freq=6.0), with freq of:
6.0 = termFreq=6.0
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.0390625 = fieldNorm(doc=580)
0.014978974 = weight(_text_:retrieval in 580) [ClassicSimilarity], result of:
0.014978974 = score(doc=580,freq=2.0), product of:
0.08963835 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.029633347 = queryNorm
0.16710453 = fieldWeight in 580, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.0390625 = fieldNorm(doc=580)
0.14285715 = coord(2/14)
- Abstract
- In our query language introduced in Part I (Journal of the American Society for Information Science and Technology. 58(2007) no.11, S.1559-1568) the user can formulate queries to find out (possibly complex) semantic relationships among entities. In this article we demonstrate the usage of our query language and discuss the new applications that it supports. We categorize several query types and give sample queries. The query types are categorized based on whether the entities specified in a query are known or unknown to the user in advance, and whether text information in documents is utilized. Natural language is used to represent the results of queries in order to facilitate correct interpretation by the user. We discuss briefly the issues related to the prototype implementation of the query language and show that an independent operation like Rho (Sheth et al., 2005; Anyanwu & Sheth, 2002, 2003), which presupposes entities of interest to be known in advance, is exceedingly inefficient in emulating the behavior of our query language. The discussion also covers potential problems, and challenges for future work.
- Source
- Journal of the American Society for Information Science and Technology. 58(2007) no.11, S.1686-1700
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval