AskMSR: Question Answering Using the Worldwide Web

By Michele Banko, Eric Brili, Susan T. Dumais, Jimmy J. Lin. 2002

75 citations recorded by the source corpus.

Subfields: Information Retrieval & Search, Natural Language Processing

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Citations in the corpus

Key-Value Memory Networks for Directly Reading Documents (2016, methodology): “Early QA systems were based on information retrieval and were designed to return snippets of text containing an answer (Voorhees and Tice, 2000; Banko et al. , 2002), with limitations in terms of question complexity and response coverage.”
Open Question Answering with Weakly Supervised Embedding Models (2014, background): “The ﬁrst successful systems transformed the questions into queries which were fed to web search engines, the answer being subsequently extracted from top returned pages or snippets [13,1].”
Improving Information Extraction by Acquiring External Evidence with Reinforcement Learning (2016, methodology): “Our approach is also close in spirit to the AskMSR system (Banko et al., 2002) which aims at using information redundancy on the web to better answer questions.”
Open question answering over curated and extracted knowledge bases (2014, background): “In 4We discard Freebase facts that are not binary relations. contrast to the semantic parsing literature [30], a oqa query is not intended to represent the complete, formal semantic interpretation of a question.”
Multi-Relational Question Answering from Narratives: Machine Reading and Reasoning in Simulated Worlds (2018, methodology): “This includes works on early information retrieval-based methods (Banko et al., 2002; Ahn et al., 2004) and methods that build on extracted structured representations from both the question and the input text (Sachan et al.”
Improving Information Extraction by Acquiring External Evidence with Reinforcement Learning by Adam Yala (2017, methodology): “Our approach is also close in spirit to the AskMSR system [2] which aims at using information redundancy on the web to better answer questions.”
Unsupervised named-entity extraction from the Web: An experimental study (2005, methodology): “This notion of redundancy-based extraction was introduced in Mulder [25] and further articulated in AskMSR [28].”