谴责
发表于 2025-3-21 16:30:36
书目名称Information Retrieval Technology影响因子(影响力)<br> http://impactfactor.cn/if/?ISSN=BK0465206<br><br> <br><br>书目名称Information Retrieval Technology影响因子(影响力)学科排名<br> http://impactfactor.cn/ifr/?ISSN=BK0465206<br><br> <br><br>书目名称Information Retrieval Technology网络公开度<br> http://impactfactor.cn/at/?ISSN=BK0465206<br><br> <br><br>书目名称Information Retrieval Technology网络公开度学科排名<br> http://impactfactor.cn/atr/?ISSN=BK0465206<br><br> <br><br>书目名称Information Retrieval Technology被引频次<br> http://impactfactor.cn/tc/?ISSN=BK0465206<br><br> <br><br>书目名称Information Retrieval Technology被引频次学科排名<br> http://impactfactor.cn/tcr/?ISSN=BK0465206<br><br> <br><br>书目名称Information Retrieval Technology年度引用<br> http://impactfactor.cn/ii/?ISSN=BK0465206<br><br> <br><br>书目名称Information Retrieval Technology年度引用学科排名<br> http://impactfactor.cn/iir/?ISSN=BK0465206<br><br> <br><br>书目名称Information Retrieval Technology读者反馈<br> http://impactfactor.cn/5y/?ISSN=BK0465206<br><br> <br><br>书目名称Information Retrieval Technology读者反馈学科排名<br> http://impactfactor.cn/5yr/?ISSN=BK0465206<br><br> <br><br>
exorbitant
发表于 2025-3-21 21:23:22
Detecting Synonymous Predicates from Online Encyclopedia with Rich Featuresure selection and their effectiveness analysis. We not only leverage different resources such as Wikipedia, Freebase, but also use different word embeddings to represent predicates. The experimental results indicate that wikitext defined by Wikipedia and predicate surface form are most useful features.
BAIL
发表于 2025-3-22 02:39:15
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原始
发表于 2025-3-22 06:46:49
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nostrum
发表于 2025-3-22 09:33:52
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harrow
发表于 2025-3-22 13:48:46
Learning a Semantic Space of Web Search via Session Datassion data, where a search session is regarded as an instantiation of an information need and keeps the interaction information of queries and URLs. Vector learning is done on a large query log from a search engine, and the efficacy of learnt vectors is examined in a few tasks.
ABYSS
发表于 2025-3-22 20:42:14
TLINE: Scalable Transductive Network Embeddingormance in node classification task, we test our methods on two real world network datasets, which are Citeseer and DBLP. The experimental result indicates that TLINE outperforms state-of-the-art baselines and is suitable for large-scale networks.
dissolution
发表于 2025-3-22 22:53:33
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debase
发表于 2025-3-23 03:10:41
Constraining Word Embeddings by Prior Knowledge – Application to Medical Information Retrievale). In this paper, we leverage the existing knowledge (word relations) in the medical domain to constrain word embeddings using the principle that related words should have similar embeddings. The resulting constrained word embeddings are used to rerank documents, showing superior effectiveness to unsupervised word embeddings.
Lipoprotein
发表于 2025-3-23 05:56:39
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