Evaluating Reference String Extraction Using Line-Based Conditional Random Fields: A Case Study with German Language Publications

Körner, Martin; Ghavimi, Behnam; Mayr, Philipp; Hartmann, Heinrich; Staab, Steffen

doi:10.1007/978-3-319-67162-8_15

Cited by 10 publications

(8 citation statements)

References 10 publications

(16 reference statements)

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“…The integrated search system is developed following the usercentered design process according to ISO 9241-201:2010 17 . Table 3 provides an overview of the performed user studies to understand the context of use, to specify user requirements, to evaluate design decisions and usability.…”

Section: User-centered Design Processmentioning

confidence: 99%

A Digital Library for Research Data and Related Information in the Social Sciences

Hienert

Kern

Boland

et al. 2019

2019 ACM/IEEE Joint Conference on Digital Libraries (JCDL)

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In the social sciences, researchers search for information on the Web, but this is most often distributed on different websites, search portals, digital libraries, data archives, and databases. In this work, we present an integrated search system for social science information that allows finding information around research data in a single digital library. Users can search for research data sets, publications, survey variables, questions from questionnaires, survey instruments, and tools. Information items are linked to each other so that users can see, for example, which publications contain data citations to research data. The integration and linking of different kinds of information increase their visibility so that it is easier for researchers to find information for re-use. In a log-based usage study, we found that users search across different information types, that search sessions contain a high rate of positive signals and that link information is often explored. CCS CONCEPTS• Information systems~Digital libraries and archives

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Section: User-centered Design Processmentioning

confidence: 99%

A Digital Library for Research Data and Related Information in the Social Sciences

Hienert

Kern

Boland

et al. 2019

2019 ACM/IEEE Joint Conference on Digital Libraries (JCDL)

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“…This is done by parsing the references that are used within a table. For this, we use the state-of-the-art PDF extraction tool GROBID [13]. GROBID focuses specifically on extracting bibliographic data from scholarly articles [19].…”

Section: Related Workmentioning

confidence: 99%

Creating a Scholarly Knowledge Graph from Survey Article Tables

Oelen

Stocker

Auer

2020

Lecture Notes in Computer Science

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Due to the lack of structure, scholarly knowledge remains hardly accessible for machines. Scholarly knowledge graphs have been proposed as a solution. Creating such a knowledge graph requires manual effort and domain experts, and is therefore time-consuming and cumbersome. In this work, we present a human-in-the-loop methodology used to build a scholarly knowledge graph leveraging literature survey articles. Survey articles often contain manually curated and high-quality tabular information that summarizes findings published in the scientific literature. Consequently, survey articles are an excellent resource for generating a scholarly knowledge graph. The presented methodology consists of five steps, in which tables and references are extracted from PDF articles, tables are formatted and finally ingested into the knowledge graph. To evaluate the methodology, 92 survey articles, containing 160 survey tables, have been imported in the graph. In total, 2 626 papers have been added to the knowledge graph using the presented methodology. The results demonstrate the feasibility of our approach, but also indicate that manual effort is required and thus underscore the important role of human experts.

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“…Instead of SVM, the approaches proposed by Patrice Lopez [13] and Körner it al. [11] use CRF to extract reference strings in view of its capability to model decision boundaries among different classes. A popular reference extracting tool, called ParsCit [5], uses a set of heuristics to identify the references by scanning the entire document for section headers such as "Reference", "Bibliography", "Notes" or any possible variations.…”

Section: Reference Extractionmentioning

confidence: 99%

An End-to-End Approach for Extracting and Segmenting High-Variance References from PDF Documents

Boukhers

Ambhore

Staab

2019

2019 ACM/IEEE Joint Conference on Digital Libraries (JCDL)

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This paper addresses the problem of extracting and segmenting references from PDF documents. The novelty of the presented approach lies in its capability to discover highly varying references mainly in terms of content, length and location in the document. Unlike existing works, the proposed method does not follow the classical pipeline that consists of sequential phases. It rather learns the different characteristics of references to be used in a coherent scheme that reduces the error accumulation by following a probabilistic approach. Contrary to conventional references, mentioning the sources of information in some publications, such as those of social science, is not subject to the same specifications such as being located in a unique reference section. Therefore, the proposed method aims to extract references of highly varying reference characteristics by relaxing the restrictions of existing methods. Additionally, we present in this paper a new challenging dataset of annotated references in German social science publications. The main purpose of this work is to serve the indexation of missing references by extracting them from challenging publications such as those of German social science. The effectiveness of the presented methods in terms of both extraction and segmentation is evaluated on different datasets, including the German social science set.

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Evaluating Reference String Extraction Using Line-Based Conditional Random Fields: A Case Study with German Language Publications

Cited by 10 publications

References 10 publications

A Digital Library for Research Data and Related Information in the Social Sciences

A Digital Library for Research Data and Related Information in the Social Sciences

Creating a Scholarly Knowledge Graph from Survey Article Tables

An End-to-End Approach for Extracting and Segmenting High-Variance References from PDF Documents

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