Thoracic
发表于 2025-3-21 16:18:34
书目名称E-Commerce, and Web Technologies影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0300062<br><br> <br><br>书目名称E-Commerce, and Web Technologies影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0300062<br><br> <br><br>书目名称E-Commerce, and Web Technologies网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0300062<br><br> <br><br>书目名称E-Commerce, and Web Technologies网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0300062<br><br> <br><br>书目名称E-Commerce, and Web Technologies被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0300062<br><br> <br><br>书目名称E-Commerce, and Web Technologies被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0300062<br><br> <br><br>书目名称E-Commerce, and Web Technologies年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0300062<br><br> <br><br>书目名称E-Commerce, and Web Technologies年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0300062<br><br> <br><br>书目名称E-Commerce, and Web Technologies读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0300062<br><br> <br><br>书目名称E-Commerce, and Web Technologies读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0300062<br><br> <br><br>
notion
发表于 2025-3-21 21:24:48
UtilSim: Iteratively Helping Users Discover Their Preferencesally updated as a user iteratively interacts with the system, helping her discover her hidden preferences in the process. We show that UtilSim, which combines domain-specific “dominance” knowledge with SimRank based similarity, significantly outperforms the existing conversational approaches using .
怎样才咆哮
发表于 2025-3-22 02:24:20
Contextual eVSM: A Content-Based Context-Aware Recommendation Framework Based on Distributional Sema the experimental evaluation we carried out an extensive series of tests in order to determine the best-performing configuration among the proposed ones. We also evaluated Contextual eVSM against a state of the art dataset, and it emerged that our framework overcomes all the baselines in most of the
美学
发表于 2025-3-22 05:47:44
Context-Aware Movie Recommendations: An Empirical Comparison of Pre-filtering, Post-filtering and Cohe recommendation algorithm used together with each contextualization approach. Nonetheless, we conclude with a number of cues and advices about which particular combinations of contextualization approaches and recommendation algorithms could be better suited for the movie recommendation domain.
争议的苹果
发表于 2025-3-22 12:18:46
Matching Ads in a Collaborative Advertising Systemordance with the proposed approach against (i) a classical content-based system and (ii) a system that relies only on the content of similar pages (disregarding the target webpage). Experimental results confirm the validity of the approach.
Desert
发表于 2025-3-22 13:02:26
Exploiting Big Data for Enhanced Representations in Content-Based Recommender Systemsnts and user profiles in a recommendation scenario. Specifically, we compared a classical keyword-based representation with two techniques that are able to map unstructured text with Wikipedia pages. The advantage of using this representation is that documents and user profiles become richer, more h
Desert
发表于 2025-3-22 18:47:12
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headlong
发表于 2025-3-22 21:34:26
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indigenous
发表于 2025-3-23 04:53:32
Evaluation of an Ordinary Share, the experimental evaluation we carried out an extensive series of tests in order to determine the best-performing configuration among the proposed ones. We also evaluated Contextual eVSM against a state of the art dataset, and it emerged that our framework overcomes all the baselines in most of the
avulsion
发表于 2025-3-23 06:51:38
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