List of Articles Extractive

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  1 - A Survey on Multi-document Summarization and Domain-Oriented Approaches
  Mahsa Afsharizadeh Hossein Ebrahimpour-Komleh Ayoub Bagheri Grzegorz  Chrupała
  10.52547/jist.16245.10.37.68
  Before the advent of the World Wide Web, lack of information was a problem. But with the advent of the web today, we are faced with an explosive amount of information in every area of search. This extra information is troublesome and prevents a quick and correct decisio More

  Before the advent of the World Wide Web, lack of information was a problem. But with the advent of the web today, we are faced with an explosive amount of information in every area of search. This extra information is troublesome and prevents a quick and correct decision. This is the problem of information overload. Multi-document summarization is an important solution for this problem by producing a brief summary containing the most important information from a set of documents in a short time. This summary should preserve the main concepts of the documents. When the input documents are related to a specific domain, for example, medicine or law, summarization faces more challenges. Domain-oriented summarization methods use special characteristics related to that domain to generate summaries. This paper introduces the purpose of multi-document summarization systems and discusses domain-oriented approaches. Various methods have been proposed by researchers for multi-document summarization. This survey reviews the categorizations that authors have made on multi-document summarization methods. We also categorize the multi-document summarization methods into six categories: machine learning, clustering, graph, Latent Dirichlet Allocation (LDA), optimization, and deep learning. We review the different methods presented in each of these groups. We also compare the advantages and disadvantages of these groups. We have discussed the standard datasets used in this field, evaluation measures, challenges and recommendations. Manuscript profile
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  2 - Modifying social impact assessment to enhance the effectiveness of company social investment strategies in contributing to local community development
  Frank  Vanclay Ilya  Gulakov Jos  Arts sh n
  Good practice social impact assessment (SIA) should lead to improved local community development outcomes. However, the social benefits alleged to flow from projects are often not as evident to affected communities as the project’s adverse impacts. Projects still give i More

  Good practice social impact assessment (SIA) should lead to improved local community development outcomes. However, the social benefits alleged to flow from projects are often not as evident to affected communities as the project’s adverse impacts. Projects still give inadequate attention to social issues and fail to achieve social development outcomes. Using a prominent gas project in Russia, the Nord Stream 2 project, as an illustrative example, we explore the potential of environmental and social impact assessment (ESIA) to enhance the effectiveness of project contributions to local community development. We analyse the main steps of the community development process for the Nord Stream 2 project, and consider how it benefitted from the SIA process. We also reflect on the potential further contribution of SIA to community development. Even though SIA and community development are interrelated, we conclude that SIA, as currently practiced, is constrained in its ability to contribute to community development outcomes. Adjustments to the SIA and corporate social investment frameworks are needed to make them more effective in achieving social development outcomes. Manuscript profile