Extracting Threshold Conceptual Structures from Web Documents
In this paper we describe an iterative approach based on formal concept analysis to refine the information retrieval process. Based on weights for ranking documents we define a weighted formal context. We use a Galois connection to introduce a new type of formal concept that allows us to work with s...
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| Main Authors: | , , |
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| Other Authors: | |
| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2015
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| Online Access: | https://hdl.handle.net/10356/81014 http://hdl.handle.net/10220/39010 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | In this paper we describe an iterative approach based on formal concept analysis to refine the information retrieval process. Based on weights for ranking documents we define a weighted formal context. We use a Galois connection to introduce a new type of formal concept that allows us to work with specific thresholds for searching words in Web documents. By increasing the threshold, we obtain smaller lattices with more relevant concepts, thus improving the retrieval of more specific items. We use techniques for processing large data sets in parallel, to generate sequences of Galois lattices, overcoming the time complexity of building a lattice for an entire large context. |
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