nitroglycerin 发表于 2025-3-28 16:55:16
Application of Fuzzy Set Theory to Extend Boolean Information Retrieval the formulation of the information needs. The aim of this con-tribution is to show how the fuzzy Boolean information retrieval models are more flexible in representing both document contents and information needs; this char-acteristics is provided by their ability to represent and manage linguistic concepts having a gradual nature.馆长 发表于 2025-3-28 21:06:52
http://reply.papertrans.cn/88/8706/870524/870524_42.pngOWL 发表于 2025-3-29 02:20:09
Large Population or Many Generations for Genetic Algorithms? Implications in Information Retrievaltical analysis providing explanation of the experimental results. The general conclusion tends to be that larger populations have better chance of significantly improving the effectiveness of retrieval.tariff 发表于 2025-3-29 04:26:23
1434-9922 formation. The aim of an IR system is to estimate the relevance of documents to users‘ information needs, expressed by means of a query. This is a very difficult and complex task, since it is pervaded with imprecision and uncertainty. Most of the existing IR systems offer a very simple model of IR,LANCE 发表于 2025-3-29 09:18:19
http://reply.papertrans.cn/88/8706/870524/870524_45.pngCursory 发表于 2025-3-29 12:45:16
A Connectionist Approach to Content Access in Documents: Application to Detection of JokesThis paper addresses the question of accessing the content of documents. Drawing from similarities between vision and language, a connectionist architecture was designed that can use context information for the “understanding” of content. The principles of the approach are illustrated by the problem of understanding jokes.倾听 发表于 2025-3-29 16:58:28
978-3-7908-2473-5Physica-Verlag Heidelberg 2000易于 发表于 2025-3-29 23:20:52
http://reply.papertrans.cn/88/8706/870524/870524_48.png变化无常 发表于 2025-3-30 02:54:52
Studies in Fuzziness and Soft Computinghttp://image.papertrans.cn/s/image/870524.jpgphotophobia 发表于 2025-3-30 04:56:38
https://doi.org/10.1007/978-3-7908-1849-9Bayesian network; algorithms; classification; data mining; fuzzy; fuzzy sets; genetic algorithms; informati