Titlebook: Web Information Systems Engineering -- WISE 2013; 14th International C Xuemin Lin,Yannis Manolopoulos,Guangyan Huang Conference proceedings

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Rodent

glans-penis

Min Peng,Jiajia Huang,Hui Fu,Jiahui Zhu,Li Zhou,Yanxiang He,Fei Lir . bezeichnet. Diese Formulierung der Aufgabenstellung ist im Falle endlicher Grundgesamtheiten unmittelbar einleuchtend und unproblematisch (s. ?Zur Bedeutung des Urnenmodells“, S. 33). Dabei werden die auf einer solchen Grundgesamtheit definierten, interessierenden Gr??en (Merkmale) als zuf?llige

東西

窩轉脊椎動物

Natwar Modani,Kuntal Dey,Ritesh Gupta,Shantanu Godbole geartete Berücksichtigung staatswissenschaftlicher. Stoffgliederung gelten lassen. Die von diesem Sesichtspunkt ausgehenden Darstellungen, welche immer-hin als ?treffliche“ anerkannt werden, enthalten nur ?Ron-glomerate“ verschiedenartiger Rechtss?tze .). Demgegenüber hat mit Otto Maner und seinen

Legion

易于出錯

A Minwise Hashing Method for Addressing Relationship Extraction from Textest neighbor classification, and leveraging a minwise hashing method for measuring similarity between relationship instances. Experiments with three different datasets that are commonly used for benchmarking relationship extraction methods show promising results, both in terms of classification performance and scalability.

CHOIR

0302-9743 th International Conference on Web Information Systems Engineering, WISE 2013, held in Nanjing, China, in October 2013. The 48 full papers, 29 short papers, and 10 demo and 5 challenge papers, presented in the two-volume proceedings LNCS 8180 and 8181, were carefully reviewed and selected from 198 s

EXALT

Community Detection in Social Media by Leveraging Interactions and Intensitiesocess on synthetic graphs. By applying the proposed approach on a topic-focused dataset of Twitter users’ interactions, we reveal communities with different features which are further analyzed to reveal and summarize the given topic’s impact on social media users.

maculated

Community Detection in Social Media by Leveraging Interactions and Intensitiesocess on synthetic graphs. By applying the proposed approach on a topic-focused dataset of Twitter users’ interactions, we reveal communities with different features which are further analyzed to reveal and summarize the given topic’s impact on social media users.