Question Answering systems & Genetic Algorithms

Tiedemann (2007), wrote an interesting paper about Genetic Algorithms, regarding how to improve passage retrieval in Question Answering systems. In this paper four selection strategies in evolutionary optimization of information retrieval (IR) in a question answering system are compared. The IR index has been enhanced by linguistic features to improve the retrieval performance of potential [...]

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Tools: OpenEphyra Question Answering System

OpenEphyra is the first open framework for question answering (QA). It retrieves accurate answers to natural language questions from the Web and other sources. OpenEphyra is hosted at SourceForge and published under the GNU General Public License (GPL). The framework comes with implementations of a number of algorithms that proved effective in CMU’s Ephyra system, [...]

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Passage Retrieval – Some Algorithms

Research in Question Answering (QA) systems has been improved by the Text Retrieval Conference (TREC) series since 1999. Almost all QA systems fielded at TREC employ some passage retrieval technique to reduce the size of the relevant document set to a manageable number of passages. Here are a bunch of algorithms that might be useful [...]

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Passage Retrieval: How to define passages

Passage Retrieval (PR) is a typical Information Retrieval (IR) system that returns short passages in response to a user query. But how to define the size and style of that short passage? It should be the paragraph where the answer probably is? Should we retrieve the whole section of the original document? Or should we [...]

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Developing: Annotating text

Previously we explained some of our “theoretical” ideas about the different development layers of prymas System. A good idea, to be a good idea, needs to be proved. So in the past days we have been concentrated in developing small prototypes to do some experiments and , later, collect and analyze the results. We assume [...]

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Information Retrieval: Text Compression

Text compression is all about finding the best way to represent an original text into fewer bytes. Text compressors try to build a reduced representation of the original source data, identifying and using the relevant structures from it. One important point is that the original source text can be restored from this reduced representation without [...]

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Some blueprints…

It works something like that: We need to build a system that is capable of automatically identifying highly relevant triples (pairs of concepts connected by a relation) over concepts from an existing ontology. By extracting relevant verbs and their grammatical arguments from a domain-specific text collection and computing corresponding relations through a combination of linguistic [...]

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Passage Retrieval vs Information Retrieval

Why choose Passage Retrieval (PR) over Information Retrieval (IR) ? Which one is the best painkiller? Information is essential. However, if we can’t find it, it really doesn’t exists. Even if we have all the documents properly stored and indexed,  our effort is wasted, unless we have reliable and fast mechanisms to look up these [...]

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Gold Rush

Usually X marks the spot, but the path for conversion of unstructured knowledge into a reliable and efficient knowledge database of facts isn’t straightforward. Despite the knowledge being already assembled in a machine-optimal-representation, information recovery into a English natural language answer isn’t trivial. Nowadays, the amount of information that companies deal with is overwhelming. Being [...]

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