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...
| Main Authors: | , , |
|---|---|
| Other Authors: | |
| Format: | Conference Paper |
| Language: | English |
| Published: |
2015
|
| Online Access: | https://hdl.handle.net/10356/81014 http://hdl.handle.net/10220/39010 |
| _version_ | 1811696411315535872 |
|---|---|
| author | Ciobanu, Gabriel Horne, Ross Vaideanu, Cristian |
| author2 | School of Computer Engineering |
| author_facet | School of Computer Engineering Ciobanu, Gabriel Horne, Ross Vaideanu, Cristian |
| author_sort | Ciobanu, Gabriel |
| collection | NTU |
| description | 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. |
| first_indexed | 2024-10-01T07:38:56Z |
| format | Conference Paper |
| id | ntu-10356/81014 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T07:38:56Z |
| publishDate | 2015 |
| record_format | dspace |
| spelling | ntu-10356/810142020-05-28T07:17:41Z Extracting Threshold Conceptual Structures from Web Documents Ciobanu, Gabriel Horne, Ross Vaideanu, Cristian School of Computer Engineering International Conference on Conceptual Structures, ICCS (21st:2014:Iaşi, Romania) 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. Accepted version 2015-12-09T04:01:38Z 2019-12-06T14:19:35Z 2015-12-09T04:01:38Z 2019-12-06T14:19:35Z 2014 Conference Paper Ciobanu, G., Horne, R., & Văideanu, C. (2015). Extracting Threshold Conceptual Structures from Web Documents. Lecture Notes in Computer Science, 8577, 130-144. https://hdl.handle.net/10356/81014 http://hdl.handle.net/10220/39010 10.1007/978-3-319-08389-6_12 en © 2014 Springer International Publishing Switzerland. This is the author created version of a work that has been peer reviewed and accepted for publication by Proceedings of the 21st International Conference on Conceptual Structures, Lecture Notes in Computer Science, Springer. It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The published version is available at: [http://dx.doi.org/10.1007/978-3-319-08389-6_12]. application/pdf |
| spellingShingle | Ciobanu, Gabriel Horne, Ross Vaideanu, Cristian Extracting Threshold Conceptual Structures from Web Documents |
| title | Extracting Threshold Conceptual Structures from Web Documents |
| title_full | Extracting Threshold Conceptual Structures from Web Documents |
| title_fullStr | Extracting Threshold Conceptual Structures from Web Documents |
| title_full_unstemmed | Extracting Threshold Conceptual Structures from Web Documents |
| title_short | Extracting Threshold Conceptual Structures from Web Documents |
| title_sort | extracting threshold conceptual structures from web documents |
| url | https://hdl.handle.net/10356/81014 http://hdl.handle.net/10220/39010 |
| work_keys_str_mv | AT ciobanugabriel extractingthresholdconceptualstructuresfromwebdocuments AT horneross extractingthresholdconceptualstructuresfromwebdocuments AT vaideanucristian extractingthresholdconceptualstructuresfromwebdocuments |