Titlebook: Switching Equipment; Hiroki Ito Reference work 2019 Springer International Publishing AG, part of Springer Nature 2019 Circuit Breaker.Vac

OBESE

书目名称Switching Equipment影响因子(影响力)




书目名称Switching Equipment影响因子(影响力)学科排名




书目名称Switching Equipment网络公开度




书目名称Switching Equipment网络公开度学科排名




书目名称Switching Equipment被引频次




书目名称Switching Equipment被引频次学科排名




书目名称Switching Equipment年度引用




书目名称Switching Equipment年度引用学科排名




书目名称Switching Equipment读者反馈




书目名称Switching Equipment读者反馈学科排名

Sarcoma

Hiroki Ito,Frank Rene Richter,Heinz Helmut Schramm query object and objects from database; the most similar objects are understood as the most relevant. However, such an automatic adoption of similarity as relevance leads to limited applicability of similarity search in domains like entity discovery, where relevant objects are not supposed to be si

无情

Lou van der Sluis,Nenad Uzelac data or divide space using hyper-planes. While searching, the mutual distances between objects and the metric properties allow for the pruning of branches with irrelevant data – this is usually implemented by utilizing selected anchor objects called pivots. Recently, we have introduced an alternati

欢乐中国

harrow

Hiroki Ito,Denis Dufournet,Anton Janssen of magnitude. While metric indexes have a hidden potential for perfecting such procedures, the construction of a suitable, fast, and incremental solution for diversified similarity searching is still an open issue. This study presents a novel index-and-search algorithm, coined ., that combines an o

雪白

invade

Denis Dufournet,Daisuke Yoshida,Sebastian Poirier,Harley Wilsonself is expensive and subject to dimensionality curse. Tensor train decomposition is designed to avoid the explosion of intermediary data, which plagues other tensor decomposition techniques. However, many tensor decomposition schemes, including tensor train decomposition is sensitive to noise in th

Charlatan

eustachian-tube

Daisuke Yoshida,Marta Lacorterovide answers autonomously. We named this task context-aware multi-document summarization (CA-MDS). Existing state-of-the-art (SOTA) solutions require truncation of the input due to the high memory demands, resulting in the loss of meaningful content. To address this issue effectively, we propose a

BLINK

David Peelo objects are represented as appropriately generated permutations of a set of pivots (or reference objects). Similarity queries are executed by searching for data objects whose permutation representation is similar to that of the query. This, of course assumes that similar objects are represented by