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Hits 81 – 100 of 360

81
Distant Reading Sentiments and Emotions in Historic German Plays
Schmidt, Thomas. - 2019
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82
Katharsis – A Tool for Computational Drametrics
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83
Inter-Rater Agreement and Usability: A Comparative Evaluation of Annotation Tools for Sentiment Annotation
Schmidt, Thomas; Winterl, Brigitte; Maul, Milena. - : Gesellschaft für Informatik e.V., 2019
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84
Stilometrie in der Rechtslinguistik. Nutzung korpuslinguistischer Verfahren für die Analyse deutschsprachiger Urteile
Auer, Anna-Maria; Berteloot, Pascale; Mielke, Bettina. - : Editions Weblaw, 2019
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85
Sentiment Annotation for Lessing’s Plays: Towards a Language Resource for Sentiment Analysis on German Literary Texts
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86
HHMM at SemEval-2019 Task 2: Unsupervised frame induction using contextualized word embeddings
Arefyev, Nikolay; Panchenko, Alexander; Anwar, Saba. - : Association for Computational Linguistics, ACL, 2019
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87
Policy preference detection in parliamentary debate motions
Abercrombie, Gavin; Ponzetto, Simone Paolo; Batista-Navarro, Riza. - : Association for Computational Linguistics, 2019
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88
Exploiting background knowledge for argumentative relation classification
Kobbe, Jonathan; Opitz, Juri; Becker, Maria. - : Leibniz-Zentrum für Informatik, 2019
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89
Using Hidden Markov Models for the accurate linguistic analysis of process model activity labels
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90
OPIEC: An open information extraction corpus
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91
On evaluating embedding models for knowledge base completion
Gemulla, Rainer; Wang, Yanjie; Broscheit, Samuel; Ruffiinelli, Daniel; Meilicke, Christian. - : Association for Computational Linguistics, 2019
Abstract: Knowledge graph embedding models have recently received significant attention in the literature. These models learn latent semantic representations for the entities and relations in a given knowledge base; the representations can be used to infer missing knowledge. In this paper, we study the question of how well recent embedding models perform for the task of knowledge base completion, i.e., the task of inferring new facts from an incomplete knowledge base. We argue that the entity ranking protocol, which is currently used to evaluate knowledge graph embedding models, is not suitable to answer this question since only a subset of the model predictions are evaluated. We propose an alternative entity-pair ranking protocol that considers all model predictions as a whole and is thus more suitable to the task. We conducted an experimental study on standard datasets and found that the performance of popular embeddings models was unsatisfactory under the new protocol, even on datasets that are generally considered to be too easy. Moreover, we found that a simple rule-based model often provided superior performance. Our findings suggest that there is a need for more research into embedding models as well as their training strategies for the task of knowledge base completion.
Keyword: 004 Informatik
URL: https://madoc.bib.uni-mannheim.de/52546/1/On%20Evaluating%20Embedding%20Models%20for%20Knowledge%20Base%20Completion.pdf
https://madoc.bib.uni-mannheim.de/52546/
https://madoc.bib.uni-mannheim.de/52546
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92
Watset: Local-global graph clustering with applications in sense and frame induction
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93
SEAGLE: A platform for comparative evaluation of semantic encoders for information retrieval
Schmidt, Fabian David; Dietsche, Markus; Ponzetto, Simone Paolo. - : Association for Computational Linguistics, 2019
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94
Multilingual and cross-lingual graded lexical entailment
Glavaš, Goran; Vulić, Ivan; Ponzetto, Simone Paolo. - : Association for Computational Linguistics, 2019
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95
Metalexicography as knowledge graph
Lindemann, David; Klaes, Christiane; Zumstein, Philipp. - : Leibniz-Zentrum für Informatik, 2019
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96
Specializing distributional vectors of all words for lexical entailment
Ponti, Edoardo Maria; Kamath, Aishwarya; Pfeiffer, Jonas. - : Association for Computational Linguistics, 2019
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97
Uncovering the semantics of Wikipedia categories
Heist, Nicolas; Paulheim, Heiko. - : Springer, 2019
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98
How to (properly) evaluate cross-lingual word embeddings: On strong baselines, comparative analyses, and some misconceptions
Glavaš, Goran; Litschko, Robert; Ruder, Sebastian. - : Association for Computational Linguistics, 2019
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99
A spreading activation framework for tracking conceptual complexity of texts
Hulpus, Ioana; Štajner, Sanja; Stuckenschmidt, Heiner. - : Association for Computational Linguistics, ACL, 2019
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100
Cross-lingual semantic specialization via lexical relation induction
Glavaš, Goran; Vulić, Ivan; Korhonen, Anna. - : Association for Computational Linguistics, 2019
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