NDLI: Semantic Pattern Transformation: Applying Knowledge Discovery Processes in Heterogeneous Domains

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Semantic Pattern Transformation: Applying Knowledge Discovery Processes in Heterogeneous Domains

Content Provider	ACM Digital Library
Author	Teufl, Peter Leitold, Herbert Posch, Reinhard
Abstract	Machine learning algorithms play in an important role in knowledge discovery due to their capability to analyze data for which only limited a priori knowledge is available. Unfortunately, their application and the extraction of information from the trained algorithm models highly depend on the nature of the analyzed data and the algorithm models. Therefore, the deployment of knowledge discovery processes in heterogeneous domains causes the requirement for time-consuming process adaptations. In this work, we argue that the value-centric feature vector representation used within machine learning is the main reason for the necessity to create such highly domain-specific setups. Therefore, the Semantic Pattern Transformation is presented, which transforms the value-centric feature vectors into a semantic representation -- the Semantic Patterns. The principle idea behind this process is to analyze the relations (co-occurrences) of feature values within the value-centric feature vectors, and use this information within a new vector-based representation -- the Semantic Patterns. The simple model used within this representation comes with many advantages, including the simplified setup procedure for arbitrary machine learning algorithms within heterogeneous domains and the simple interpretation of the underlying model. We have already successfully applied the Semantic Pattern Transformation in numerous applications including text analysis, event correlation, malware detection, analysis of Twitter data and Android application analysis. This work extends the application-oriented works by a detailed explanation of the method and a thorough evaluation of supervised and unsupervised learning scenarios, and the application within semantic-aware search algorithms.
Starting Page	1
Ending Page	8
Page Count	8
File Format	PDF
ISBN	9781450323000
DOI	10.1145/2494188.2494194
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2013-09-04
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Semantic patterns Semantic pattern transformation Associative networks Spreading activation
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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