Evaluation of Scientific Elements for Text Similarity in Biomedical Publications

Neves, Mariana; Butzke, Daniel; Grune, Barbara

doi:10.18653/v1/w19-4515

Cited by 12 publications

(18 citation statements)

References 37 publications

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“…We recently published a study in which we compared four tools for the extraction of the zones and evaluated them on seven use studies (https://github.com/mariananeves/scientific-elements-text-similarity) [5]. Our study also demonstrated that using pre-selected zones, instead of the whole abstracts, yields better performance in the ranking task.…”

Section: The Web Applicationmentioning

confidence: 78%

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Integration of the PubAnnotation ecosystem in the development of a web-based search tool for alternative methods

Neves¹

2020

Genomics Inform

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Finding publications that propose alternative methods to animal experiments is an important but time-consuming task since researchers need to perform various queries to literature databases and screen many articles to assess two important aspects: the relevance of the article to the research question, and whether the article's proposed approach qualifies to being an alternative method. We are currently developing a Web application to support finding alternative methods to animal experiments. The current (under development) version of the application utilizes external tools and resources for document processing, and relies on the PubAnnotation ecosystem for annotation querying, annotation storage, dictionary-based tagging of cell lines, and annotation visualization. Currently, our two PubAnnotation repositories for discourse elements contain annotations for more than 110k PubMed documents. Further, we created an annotator for cell lines that contain more than 196k terms from Cellosaurus. Finally, we are experimenting with TextAE for annotation visualization and for user feedback.

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Section: The Web Applicationmentioning

confidence: 78%

“…However, given that not all abstracts in PubMed are structured, we automatically extract the zones for the remaining articles using the ArguminSci tool [6]. This was the best performing tool according to our study [5].…”

Section: The Web Applicationmentioning

confidence: 99%

Integration of the PubAnnotation ecosystem in the development of a web-based search tool for alternative methods

Neves¹

2020

Genomics Inform

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“…Thus far, we have identified 15 `critical´ semantic types and have projected them onto a `master chart´. Futhermore, "zoning" of abstracts and elimination of sections that focus on methodology during preprocessing may also improve the selection of `relevantṕ ublications in the hitlist, by reversing any `negative selection´ due to alternative methodology (27).…”

Section: Discussionmentioning

confidence: 99%

“…The scientific entities or elements exploited by us to consider the `equivalence´ of biomedical research are essentially different from the ones used by other groups to distinguish research. Please see (10) for a comprehensive survey of such elements and annotated corpora Furthermore, we wondered whether it would be possible, to assign individual `critical´ scientific elements (i.e. original words from abstracts) to semantic types of the Unified Medical Language System (UMLS) semantic network (11) that would be generally `critical´ for any analysis of equivalence´ in the biomedical domain (e.g.…”

Section: Introducing the Smafira Projectmentioning

confidence: 99%

SMAFIRA-c: A benchmark text corpus for evaluation of approaches to relevance ranking and knowledge discovery in the biomedical domain

Butzke¹,

Dulisch²,

Dunst³

et al. 2020

Preprint

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Background The engineering of elaborate and innovative tools to navigate the ever growing biomedical knowledge base, instanced in PubMed/Medline, must be guided by genuine case studies addressing `real world´ user needs. Furthermore, algorithm-based predictions regarding `similarity´, `relatedness´ or `relevance´ of pieces of information (e.g. relevance ranking) should be transparent and comprehensible to users. Results We here present a corpus of abstracts (n = 300) annotated on document level representing three case studies in the experimental biomedical domain. The SMAFIRA corpus mirrors `real-world´ information retrieval needs, i.e. the identification of potential alternatives to given animal experiments that support `equivalent´ scientific purposes while using basically different experimental methodology. Since in most cases not even the authors of `relevant´ research papers are aware of such a possible implication of their experimental approaches, our case studies actually illustrate knowledge discovery. Annotation of abstracts (regarding `equivalence´) was conducted by one researcher with broad domain knowledge (in one case study supported by a second opinion from a domain expert) and was informed by a newly created model describing distinguishable stages in experimental biomedicine. Furthermore, such stages were linked to generic scientific purposes. This perspective thus may share some commonalities with topic modelling approaches. Annotation of `relevance´ (i.e. `equivalence´ of scientific purpose plus alternative methodology) relied on expert knowledge in the domain of animal use alternatives. The case studies were used for an evaluation of rankings which were provided by the `similar articles´ algorithm employed in PubMed. Conclusions Building on approved techniques utilized in the domain of intellectual property, we have adapted the concept of `equivalence´ to support a transparent, reproducible and stringent comparison of biomedical textual documents with regards to the implied scientific objectives. This concept may allow for text mining with improved resolution and may aid the retrieval of appropriate animal use alternatives. Computer science researchers in the field of biomedical knowledge discovery may also use our corpus, which is designed to grow essentially in the near future, as a reliable and informative benchmark for the evaluation of algorithms supporting such a goal. Annotations are available from GitHub.

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“…Rhetorical Structure Theory [15] describes discourse coherence relations. For mining scientific abstracts and full-text articles, researchers have developed a variety of types of text classification schemes described as rhetorical, e.g., see the survey in [17]. But none of the above is concerned with rhetorical analysis in the sense of this proposal, which is informed by computational and classical rhetoricians.…”

Section: Related Workmentioning

confidence: 99%

Recognizing rhetoric in science policy arguments

Green

2020

AAC

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Diligent citizens must critically analyze arguments for science policy recommendations, such as cutting greenhouse gas emissions or growing genetically modified food crops. Science policy articles present arguments for and against such recommendations using scientific evidence and rhetorical devices. In this paper we present an in-depth analysis of argumentation and rhetorical devices in two journal articles on climate change issues. One objective was to gain a better understanding of use of rhetorical devices in this genre, as a prerequisite for designing and building a rhetorically-annotated digital corpus of full-text science policy articles. The near term objective was to inform the design of pedagogical tools to help students analyze science policy arguments.

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Evaluation of Scientific Elements for Text Similarity in Biomedical Publications

Cited by 12 publications

References 37 publications

Integration of the PubAnnotation ecosystem in the development of a web-based search tool for alternative methods

Integration of the PubAnnotation ecosystem in the development of a web-based search tool for alternative methods

SMAFIRA-c: A benchmark text corpus for evaluation of approaches to relevance ranking and knowledge discovery in the biomedical domain

Recognizing rhetoric in science policy arguments

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