Information classification and navigation based on 5W1H of the target information

Ikeda, Teruaki; Okumura, Akitoshi; Muraki, Kazunori

doi:10.3115/980845.980940

Cited by 6 publications

(3 citation statements)

References 5 publications

(4 reference statements)

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“…5W1H, which stands for Why, Who, When, Where, What, and How, has been broadly employed in journalism to gather information (Chung et al, 2009). 5W1H can be used also to classify and navigate information with intuitive classification axes and retrieval keys (Ikeda et al, 1998). Hong and Davison (2009) used 5W1H as a classification method for their experiment on question answering in discussion boards.…”

Section: Requirements For Classification Schemementioning

confidence: 99%

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A framework for research inventory of manufacturing sustainability assessment

Lee¹,

Lee²

2013

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There have been many research papers focused on development of guidelines, indicators, metrics, methods, tools, and systemsall related to sustainability performance assessment. However, manufacturing companies have difficulty in finding papers that are relevant to their sustainability goals and conditions. A research inventory is a data repository for storing research papers in a manner that makes them easy to retrieve. To be successful, therefore, the inventory must have a system for managing, in a systematic manner, the results generated by a large number of researchers around the world. In this paper, we propose a framework for a research inventory that focuses on papers that report on research related to manufacturing sustainability assessment. This proposed framework consists of two parts: an operational definition and a classification scheme. The definition distinguishes between those papers that belong in the inventory and those that do not. The classification scheme is used to tag/code papers for retrieval. We demonstrate the use of this proposed framework using the Sustainable Manufacturing Toolkit of Organization for Economic Cooperation and Development.

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Section: Requirements For Classification Schemementioning

confidence: 99%

“…Huang et al (2011) proposed a scheme based on the context of 5W1H in ubiquitous computing to establish a database for environmental monitoring factors. Ikeda et al (1998) proposed a method by which 5WlH information is used to classify and navigate Japanese language texts.…”

Section: Requirements For Classification Schemementioning

confidence: 99%

A framework for research inventory of manufacturing sustainability assessment

Lee¹,

Lee²

2013

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“…5W1H approach classifies the dimensions of a query in six dimensions, namely: (i) WHO: (human/participants); (ii) WHAT: (object/content); (iii) WHEN: (time); (iv) WHERE: (space/location), (v) WHY: (purpose/behavior); and (vi) HOW: (behavior/form). See [87][88][89][90] for additional discussion of structuring queries and knowledge-base using the 5W1H approach.…”

Section: Native Queries Based On 5w1h Approachmentioning

confidence: 99%

EpiK: A Knowledge Base for Epidemiological Modeling and Analytics of Infectious Diseases

Hasan

Fox

Bisset

et al. 2017

J Healthc Inform Res

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Computational epidemiology seeks to develop computational methods to study the distribution and determinants of health-related states or events (including disease), and the application of this study to the control of diseases and other health problems. Recent advances in computing and data sciences have led to the development of innovative modeling environments to support this important goal. The datasets used to drive the dynamic models as well as the data produced by these models presents unique challenges owing to their size, heterogeneity and diversity. These datasets form the basis of effective and easy to use decision support and analytical environments. As a result, it is important to develop scalable data management systems to store, manage and integrate these datasets. In this paper, we develop EpiK-a knowledge base that facilitates the development of decision support and analytical environments to support epidemic science. An important goal is to develop a framework that links the input as well as output datasets to facilitate effective spatio-temporal and social reasoning that is critical in planning and intervention analysis before and during an epidemic. The data management framework links modeling workflow data and its metadata using a controlled vocabulary. The metadata captures information about storage, the mapping between the linked model and the physical layout, and relationships to support services. EpiK is designed to support agent-based modeling and analytics frameworks-aggregate models can be seen as special cases and are thus supported. We use semantic web technologies to create a representation of the datasets that encapsulates both the location and the schema heterogeneity. The choice of RDF as a representation language is motivated by the diversity and growth of the datasets that need to be integrated. A query bank is developed-the queries capture a broad range of questions that can be posed and answered during a typical case study pertaining to disease outbreaks. The queries are constructed using SPARQL Protocol and RDF Query Language (SPARQL) over the EpiK. EpiK can hide schema and location heterogeneity while efficiently supporting queries that span the computational epidemiology modeling pipeline: from model construction to simulation output. We show that the performance of benchmark queries varies significantly with respect to the choice of hardware underlying the database and resource description framework (RDF) engine.

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Target Concept Analysis

Hamborg

2022

Revealing Media Bias in News Articles

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This chapter details the first component of person-oriented framing analysis: target concept analysis. This component aims to find and resolve mentions of persons, which can be subject to media bias. The chapter introduces and discusses two approaches for this task. First, the chapter introduces an approach for event extraction. The approach extracts answers to the journalistic 5W1H questions, i.e., who did what, when, where, why, and how. The in-text answers to these questions describe a news article’s main event. Afterward, the chapter introduces an approach that is the first to resolve highly context-dependent coreferences across news articles as they commonly occur in the presence of sentence-level bias forms. Our approach can resolve mentions that are coreferential also only in coverage on the same event and that otherwise may even be contradictory, such as “attack” or “self-defense” and “riot” or “protest.” Lastly, the chapter argues for using the latter approach for the target concept analysis component, in particular because of its high classification performance. Another reason for our decision is that using the event extraction approach in the target concept analysis component would require the development of a subsequent approach, i.e., to compare the events extracted from individual articles and resolve them across all articles.

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Information classification and navigation based on 5W1H of the target information

Cited by 6 publications

References 5 publications

A framework for research inventory of manufacturing sustainability assessment

A framework for research inventory of manufacturing sustainability assessment

EpiK: A Knowledge Base for Epidemiological Modeling and Analytics of Infectious Diseases

Target Concept Analysis

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