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Showing 1 to 13 of 13 for “"Distant supervision"”.
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Indirect supervision for relation extraction using question-answer pairs
… acquired by linking to knowledge bases (distant supervision). However, due to the incompleteness of knowledge bases and the context-agnostic labeling, the training data collected via distant supervision (DS) can be very noisy. In recent years, as increasing attention has been brought to …
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Contextual lexicon-based sentiment analysis for social media.
… a domain-specific lexicon is generated using a distant supervision method and integrated with a general-purpose lexicon, using a weighted strategy, to form a hybrid (domain-adapted) lexicon. This has the dual purpose of enriching term coverage of the general purpose lexicon with non-standard but …
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Mining entity and relation structures from text: An effort-light approach
… infer types for entity mentions by propagating ""distant supervision"" (from external knowledge bases) via relational phrases. In order to resolve data sparsity issue during propagation, we complement the type propagation with clustering of functionally similar relational phrases based on their …
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Event Detection and Extraction from News Articles
… an MIMTRNN model for event extraction with distant supervision to overcome the problem of lacking fine level labels and small size training data. The proposed MIMTRNN model systematically integrates the RNN, Multi-Instance Learning, and Multi-Task Learning into a unified framework. The RNN …
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Integrating local context and global cohesiveness for open information extraction
… structural signal in a unified framework with distant supervision. The new system can be efficiently applied to different domains as it uses facts from external knowledge bases as supervision; and can effectively score sentence-level tuple extractions based on corpus-level statistics. …
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Efficient Information Extraction Using Statistical Relational Learning
… alleviate this problem by employing some form of distant supervision. In this work, we take a different approach -- we create weakly supervised examples for relations by using commonsense knowledge. The key innovation is that this commonsense knowledge is completely independent of the natural …
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Modeling phones, keywords, topics and intents in spoken languages
… with the help of mismatched-crowdsourcing- based distant supervision, linguistic knowledge, and corpus-based transfer learning. First we analyze the usefulness of mismatched transcripts and distinctive features, and then propose phone recognition based on the optimized inference of the phone set …
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Interpretable local citation recommendation
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-09-16 without embargo terms
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Entity Information Extraction using Structured and Semi-structured resources
… facts, called TSRF which is trained on distant supervision based on the largest semi-structured resource available: Wikipedia. TSRF employs language models consisting of patterns automatically bootstrapped from sentences collected from Wikipedia pages that contain the main entity of a …
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Controlling the effect of crowd noisy annotations in NLP Tasks
… deals with design a benchmark for evaluation Distant Supervision (DS) for relation extraction task. We propose a baseline which involves training a simple yet accurate one-vs-all strategy using SVM classifier. Moreover, we exploit automatic feature extraction technique using convolutional tree …
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End-to-End Relation Extraction via Syntactic Structures and Semantic Resources
… is hindered by well-known problems such as heavy supervision and scalability. These drawbacks can be alleviated by applying a form of weakly supervision, specifically named distant supervision (DS), to automatically derive explicit facts from the semi-structured part of Wikipedia. To learn …
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Constructing and mining structured heterogeneous information networks from massive text corpora
… the need for heavy human annotation, utilize distant supervision from existing, open knowledge bases and statistical signals (e.g., frequency and point-wise mutual information) based on massive corpora. Such approaches are therefore general, extensible to texts corpora in multiple languages …
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Scientific knowledge extraction from massive text data
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-04-12 without embargo terms