Please use this identifier to cite or link to this item:
https://idr.nitk.ac.in/jspui/handle/123456789/8096
Title: | Frame instance extraction and clustering for default knowledge building |
Authors: | Shah, A. Basile, V. Cabrio, E. Sowmya, Kamath S. |
Issue Date: | 2017 |
Citation: | CEUR Workshop Proceedings, 2017, Vol.1935, , pp.1-10 |
Abstract: | Obtaining and representing common-sense knowledge, useful in a robotics scenario for planning and making inference about the robots' surroundings, is a challenging problem, because such knowledge is typically found in unstructured repositories such as text corpora or small handmade resources. The work described in this paper presents a methodology for automatically creating a default knowledge base about real-world objects for the robotics domain. The proposed method relies on clustering frame instances extracted from natural language text as a way of distilling default knowledge. We collect and parse a natural language corpus using the Web as a source, then perform an agglomerative clustering of frame instances according to an appropriately defined similarity measure, and finally extract prototypical frame instances from each cluster and publish them in LOD-complaint format to promote reuse and interoperability. |
URI: | https://idr.nitk.ac.in/jspui/handle/123456789/8096 |
Appears in Collections: | 2. Conference Papers |
Files in This Item:
File | Description | Size | Format | |
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7 Frame Instance Extraction.pdf | 272.02 kB | Adobe PDF | View/Open |
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