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Knowledge-Based Weak Supervision for Information Extraction of Overlapping Relations
Information extraction (IE) holds the promise of generating a large-scale knowledge base from the Web's natural language text. Knowledge-based weak supervision, using structured data to heuristicallyExpand
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Learning 5000 Relational Extractors
Many researchers are trying to use information extraction (IE) to create large-scale knowledge bases from natural language text on the Web. However, the primary approach (supervised learning ofExpand
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Harvesting Parallel News Streams to Generate Paraphrases of Event Relations
The distributional hypothesis, which states that words that occur in similar contexts tend to have similar meanings, has inspired several Web mining algorithms for paraphrasing semanticallyExpand
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Exploiting Parallel News Streams for Unsupervised Event Extraction
Most approaches to relation extraction, the task of extracting ground facts from natural language text, are based on machine learning and thus starved by scarce training data. Manual annotation isExpand
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Machine Reading at the University of Washington
Machine reading is a long-standing goal of AI and NLP. In recent years, tremendous progress has been made in developing machine learning approaches for many of its subtasks such as parsing,Expand
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Adaptive Parser-Centric Text Normalization
Text normalization is an important first step towards enabling many Natural Language Processing (NLP) tasks over informal text. While many of these tasks, such as parsing, perform the best over fullyExpand
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A Novel Web Page Categorization Algorithm Based on Block Propagation Using Query-Log Information
Most existing web page classification algorithms, including content-based, link-based, or query-log analysis methods, treat the pages as smallest units. However, web pages usually contain some noisyExpand
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Ontological Smoothing for Relation Extraction with Minimal Supervision
Relation extraction, the process of converting natural language text into structured knowledge, is increasingly important. Most successful techniques use supervised machine learning to generateExpand
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Web-scale classification with naive bayes
Traditional Naive Bayes Classifier performs miserably on web-scale taxonomies. In this paper, we investigate the reasons behind such bad performance. We discover that the low performance are notExpand
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Software bug localization with markov logic
Software bug localization is the problem of determining buggy statements in a software system. It is a crucial and expensive step in the software debugging process. Interest in it has grown rapidlyExpand
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