NDLI: Integrating knowledge capture and supervised learning through a human-computer interface

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Knowledge capture through the millennia: from cuneiform to the semantic web

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From mappings to modules: using mappings to identify domain-specific modules in large ontologies

Quality assurance of the content of a large DL-based terminology using mixed lexical and semantic criteria: experience with SNOMED CT

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Multipedia: enriching DBpedia with multimedia information

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Acquiring OWL ontologies from XML documents

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Let's agree to disagree: on the evaluation of vocabulary alignment

Integrating knowledge capture and supervised learning through a human-computer interface

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On the role of user-generated metadata in audio visual collections

Eliciting hierarchical structures from enumerative structures for ontology learning

An analysis of collaborative patterns in large-scale ontology development projects

Experience with long-term knowledge acquisition

Predicting adverse events: detecting myocardial damage in intensive care unit (ICU) patients

Boundary detection of multiple related temporal duration of schedules in email

Extracting relevant questions to an RDF dataset using formal concept analysis

Language resources extracted from Wikipedia

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Interpreting relational databases in the RDF domain

Linked open piracy

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Guided creation and update of objects in RDF(S) bases

LinkedDataLens: linked data as a network of networks

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Capturing missing edges in social networks using vertex similarity

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Integrating knowledge capture and supervised learning through a human-computer interface

Content Provider	ACM Digital Library
Author	Kunapuli, Gautam Page, David Walker, Trevor Larsen, Noah Shavlik, Jude
Abstract	Some supervised-learning algorithms can make effective use of domain knowledge in addition to the input-output pairs commonly used in machine learning. However, formulating this additional information often requires an in-depth understanding of the specific knowledge representation used by a given learning algorithm. The requirement to use a formal knowledge-representation language means that most domain experts will not be able to articulate their expertise, even when a learning algorithm is capable of exploiting such valuable information. We investigate a method to ease this knowledge acquisition through the use of a graphical, human-computer interface. Our interface allows users to easily provide advice about specific examples, rather than requiring them to provide general rules; we leave the task of properly generalizing such advice to the learning algorithms. We demonstrate the effectiveness of our approach using the Wargus real-time strategy game, comparing learning with no advice to learning with concrete advice provided through our interface, as well as comparing to using generalized advice written by an AI expert. Our results show that our approach of combining a GUI-based advice language with an advice-taking learning algorithm is an effective way to capture domain knowledge.
Starting Page	89
Ending Page	96
Page Count	8
File Format	PDF
ISBN	9781450303965
DOI	10.1145/1999676.1999693
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2011-06-26
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Human-computer interface Advice taking
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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