About: Temporal event searches based on event maps and relationships()

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An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	Temporal event searches based on event maps and relationships()
Creator	Li, Qing Cai, Yi Wong, Tak-Lam Xie, Haoran Lau, Raymond Wang, Fu
source	Elsevier; Medline; PMC
abstract	To satisfy a user’s need to find and understand the whole picture of an event effectively and efficiently, in this paper we formalize the problem of temporal event searches and propose a framework of event relationship analysis for search events based on user queries. We define three kinds of event relationships: temporal, content dependence, and event reference, that can be used to identify to what extent a component event is dependent on another in the evolution of a target event (i.e., the query event). The search results are organized as a temporal event map (TEM) that serves as the whole picture about an event’s evolution or development by showing the dependence relationships among events. Based on the event relationships in the TEM, we further propose a method to measure the degrees of importance of events, so as to discover the important component events for a query, as well as the several algebraic operators involved in the TEM, that allow users to view the target event. Experiments conducted on a real data set show that our method outperforms the baseline method Event Evolution Graph (EEG), and it can help discover certain new relationships missed by previous methods and even by human annotators.
has issue date	2019-09-25(xsd:dateTime)
bibo:doi	10.1016/j.asoc.2019.105750
bibo:pmid	32288693
has license	no-cc
sha1sum (hex)	d34c5f3a5f439702d5c04a9c11b8b5c18d869151
schema:url	https://doi.org/10.1016/j.asoc.2019.105750
resource representing a document's title	Temporal event searches based on event maps and relationships()
has PubMed Central identifier	PMC7105191
has PubMed identifier	32288693
schema:publication	Appl Soft Comput
resource representing a document's body	covid:d34c5f3a5f439702d5c04a9c11b8b5c18d869151#body_text
is schema:about of	named entity 'RELATIONSHIPS' named entity 'event' named entity 'events' named entity 'evolution' named entity 'serves' named entity 'real' named entity 'notations' named entity 'baseline' named entity 'smoothly' named entity 'Temporal' named entity 'RELATIONSHIPS' named entity 'DEPENDENT' named entity 'DEGREES' named entity 'OPERATIONS' named entity 'EXTENT' named entity 'ALLOW' named entity 'TEMPORAL' named entity 'NEED' named entity 'RELATIONSHIP' named entity 'CASE STUDIES' named entity 'TABLES' named entity 'USED' named entity 'WHAT' named entity 'CONSTRUCTION' named entity 'PUBLISHED' named entity 'UNDERSTAND' named entity '5B1' named entity 'DATA SET' named entity 'BASED' named entity 'LITERATURE REVIEW' named entity 'EVENTS' named entity 'PICTURE' named entity 'SEARCH RESULTS' named entity 'TEM' named entity '282' named entity 'REFERENCE' named entity 'MISSED' named entity 'MAPS' named entity 'EVENT' named entity 'DISCOVER' named entity 'METHOD' named entity 'QUERY' named entity 'MAKE' named entity 'VERSION' named entity 'FIGURES' named entity '27S' named entity 'TARGET' named entity 'HUMAN' named entity 'TEMPORAL' named entity 'PROBLEM' named entity '283' named entity 'OUR' named entity 'REUSED' named entity 'METRICS' named entity 'TO MEASURE' named entity 'COMPONENT' named entity 'GRAPH' named entity '28I' named entity 'HELP' named entity 'ORGANIZED' named entity 'ANALYSIS' named entity 'SEARCH' named entity 'PAPER' named entity 'IMPORTANT' named entity 'CONTENT' named entity 'EXPERIMENTS' named entity 'COMPREHENSIVE' named entity 'NEW' named entity 'ARTICLE' named entity 'MAP' named entity 'VIEW' named entity 'INVOLVED' named entity 'USER' named entity 'BASED' named entity 'RANKING' named entity 'EXTENSION'

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