carbohydrate 发表于 2025-3-25 04:25:02
http://reply.papertrans.cn/47/4698/469734/469734_21.pngBILIO 发表于 2025-3-25 09:23:45
http://reply.papertrans.cn/47/4698/469734/469734_22.png格子架 发表于 2025-3-25 15:17:14
http://reply.papertrans.cn/47/4698/469734/469734_23.png异端 发表于 2025-3-25 19:17:17
http://reply.papertrans.cn/47/4698/469734/469734_24.png骑师 发表于 2025-3-25 22:49:23
Prediction of Relevance between Requests and Web Services Using ANN and LR Modelsmethods. The experimental results show the efficiency of both methods in predicting the new cases. However, Artificial Neural Network with sensitivity analysis model outperforms Logistic Regression method.幼稚 发表于 2025-3-26 02:43:02
Orienteering Problem Modeling for Electric Vehicle-Based Tour included in the population. The performance measurement result obtained from a prototype implementation discovers that the proposed service can include 95 % of selected spots in the final schedule on the typical tour scenario for the given inter-destination and stay time distribution.cumulative 发表于 2025-3-26 07:32:56
A Semantically Enhanced Tag-Based Music Recommendation Using Emotion Ontologyollected from last.fm. The conventional track-based recommendation, the unweighted tag-based recommendation, and the weighted tag-based recommendation are compared in terms of precision. Our experimental results show that the weighted tag-based recommendation outperforms other two approaches in terms of precision.雪上轻舟飞过 发表于 2025-3-26 11:43:51
http://reply.papertrans.cn/47/4698/469734/469734_28.pngCeliac-Plexus 发表于 2025-3-26 12:56:58
Recommending QA Documents for Communities of Question-Answering Websitesembers’ reputations, the push scores and collection time of QAs, the complementary relationships between QAs and their relevance to the communities. Experimental results show that the proposed method outperforms other conventional methods, providing a more effective manner to recommend QA documents to knowledge communities.glans-penis 发表于 2025-3-26 17:39:56
A Method for Collaborative Recommendation in Document Retrieval Systemsdology of experimental evaluation was presented and simulations were performed. The preliminary experiments have shown that the most important demographic attributes are gender, age, favorite browser and level of education.