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Title: API Requirements for Dynamic Graph Prediction

Abstract

Given a large-scale time-evolving multi-modal and multi-relational complex network (a.k.a., a large-scale dynamic semantic graph), we want to implement algorithms that discover patterns of activities on the graph and learn predictive models of those discovered patterns. This document outlines the application programming interface (API) requirements for fast prototyping of feature extraction, learning, and prediction algorithms on large dynamic semantic graphs. Since our algorithms must operate on large-scale dynamic semantic graphs, we have chosen to use the graph API developed in the CASC Complex Networks Project. This API is supported on the back end by a semantic graph database (developed by Scott Kohn and his team). The advantages of using this API are (i) we have full-control of its development and (ii) the current API meets almost all of the requirements outlined in this document.

Authors:
;
Publication Date:
Research Org.:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1036864
Report Number(s):
UCRL-TR-225656
TRN: US201207%%44
DOE Contract Number:  
W-7405-ENG-48
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICAL METHODS AND COMPUTING; ALGORITHMS; FORECASTING; LEARNING; PROGRAMMING

Citation Formats

Gallagher, B, and Eliassi-Rad, T. API Requirements for Dynamic Graph Prediction. United States: N. p., 2006. Web. doi:10.2172/1036864.
Gallagher, B, & Eliassi-Rad, T. API Requirements for Dynamic Graph Prediction. United States. doi:10.2172/1036864.
Gallagher, B, and Eliassi-Rad, T. Fri . "API Requirements for Dynamic Graph Prediction". United States. doi:10.2172/1036864. https://www.osti.gov/servlets/purl/1036864.
@article{osti_1036864,
title = {API Requirements for Dynamic Graph Prediction},
author = {Gallagher, B and Eliassi-Rad, T},
abstractNote = {Given a large-scale time-evolving multi-modal and multi-relational complex network (a.k.a., a large-scale dynamic semantic graph), we want to implement algorithms that discover patterns of activities on the graph and learn predictive models of those discovered patterns. This document outlines the application programming interface (API) requirements for fast prototyping of feature extraction, learning, and prediction algorithms on large dynamic semantic graphs. Since our algorithms must operate on large-scale dynamic semantic graphs, we have chosen to use the graph API developed in the CASC Complex Networks Project. This API is supported on the back end by a semantic graph database (developed by Scott Kohn and his team). The advantages of using this API are (i) we have full-control of its development and (ii) the current API meets almost all of the requirements outlined in this document.},
doi = {10.2172/1036864},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2006},
month = {10}
}

Technical Report:

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