Building an Argument Search Engine for the Web
Henning Wachsmuth,Martin Potthast,Khalid Al Khatib,Yamen Ajjour,Jana Puschmann,Jiani Qu,Jonas Dorsch,Viorel Morari,Janek Bevendorff,Benno Stein +9 more
- pp 49-59
TLDR
An argument search framework for studying how people query for arguments, how to mine arguments from the web, or how to rank them is developed and a prototype search engine is built that relies on an initial, freely accessible index of nearly 300k arguments crawled from reliable web resources.Abstract:
Computational argumentation is expected to play a critical role in the future of web search. To make this happen, many search-related questions must be revisited, such as how people query for arguments, how to mine arguments from the web, or how to rank them. In this paper, we develop an argument search framework for studying these and further questions. The framework allows for the composition of approaches to acquiring, mining, assessing, indexing, querying, retrieving, ranking, and presenting arguments while relying on standard infrastructure and interfaces. Based on the framework, we build a prototype search engine, called args, that relies on an initial, freely accessible index of nearly 300k arguments crawled from reliable web resources. The framework and the argument search engine are intended as an environment for collaborative research on computational argumentation and its practical evaluation.read more
Citations
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Journal ArticleDOI
Argument Mining: A Survey
John Lawrence,Chris Reed +1 more
TL;DR: The techniques that establish the foundations for argument mining are explored, a review of recent advances in argument mining techniques are provided, and the challenges faced in automatically extracting a deeper understanding of reasoning expressed in language in general are discussed.
Proceedings ArticleDOI
Cross-topic Argument Mining from Heterogeneous Sources
TL;DR: This paper proposes a new sentential annotation scheme that is reliably applicable by crowd workers to arbitrary Web texts and shows that integrating topic information into bidirectional long short-term memory networks outperforms vanilla BiLSTMs in F1 in two- and three-label cross-topic settings.
Proceedings ArticleDOI
ArgumenText: Searching for Arguments in Heterogeneous Sources
Christian Stab,Johannes Daxenberger,Chris Stahlhut,Tristan Miller,Benjamin Schiller,Christopher Tauchmann,Steffen Eger,Iryna Gurevych +7 more
TL;DR: This paper presents an argument retrieval system capable of retrieving sentential arguments for any given controversial topic, and finds that its system covers 89% of arguments found in expert-curated lists of arguments from an online debate portal, and also identifies additional valid arguments.
Proceedings ArticleDOI
Seeing Things from a Different Angle: Discovering Diverse Perspectives about Claims.
TL;DR: A thorough analysis of the dataset is provided to highlight key underlying language understanding challenges, and it is shown that human baselines across multiple subtasks far outperform ma-chine baselines built upon state-of-the-art NLP techniques.
Proceedings ArticleDOI
Retrieval of the Best Counterargument without Prior Topic Knowledge
TL;DR: This work hypothesizes the best counterargument to invoke the same aspects as the argument while having the opposite stance, and simultaneously model the similarity and dissimilarity of pairs of arguments, based on the words and embeddings of the arguments’ premises and conclusions.
References
More filters
Journal ArticleDOI
The anatomy of a large-scale hypertextual Web search engine
Sergey Brin,Lawrence Page +1 more
TL;DR: This paper provides an in-depth description of Google, a prototype of a large-scale search engine which makes heavy use of the structure present in hypertext and looks at the problem of how to effectively deal with uncontrolled hypertext collections where anyone can publish anything they want.
Proceedings Article
The PageRank Citation Ranking : Bringing Order to the Web
TL;DR: This paper describes PageRank, a mathod for rating Web pages objectively and mechanically, effectively measuring the human interest and attention devoted to them, and shows how to efficiently compute PageRank for large numbers of pages.
Journal Article
The Anatomy of a Large-Scale Hypertextual Web Search Engine.
Sergey Brin,Lawrence Page +1 more
TL;DR: Google as discussed by the authors is a prototype of a large-scale search engine which makes heavy use of the structure present in hypertext and is designed to crawl and index the Web efficiently and produce much more satisfying search results than existing systems.
Book
Introduction to Information Retrieval
TL;DR: In this article, the authors present an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections.
Book
The uses of argument
TL;DR: In this paper, the origins of epistemological theory are discussed and the layout of argument and modal arguments are discussed, as well as the history of working logic and idealised logic.