Between information retrieval services and bibliometrics research. New ways of semantic browsing and visual analytics
•Télécharger en tant que PPTX, PDF•
2 j'aime•526 vues
R. Koopman, S. Wang, A. Scharnhorst (2015) Between information retrieval services and bibliometrics research. New ways of semantic browsing and visual analytics. Presentation at the Sigmetrics workshop, ASIST 2015, November 7, 2015 St. Louis, Missouri
Recommandé
Recommandé
Contenu connexe
Tendances
Tendances (20)
En vedette
En vedette (14)
Similaire à Between information retrieval services and bibliometrics research. New ways of semantic browsing and visual analytics
Similaire à Between information retrieval services and bibliometrics research. New ways of semantic browsing and visual analytics (20)
Plus de Andrea Scharnhorst
Plus de Andrea Scharnhorst (19)
Dernier
Dernier (20)
Between information retrieval services and bibliometrics research. New ways of semantic browsing and visual analytics
- 1. Between information retrieval services and bibliometrics research – new ways of semantic browsing and visual analytics Rob Koopman, Shenghui Wang OCLC Research Andrea Scharnhorst DANS- KNAW November 7, 2015 ASIST, sigmetrics workshop
- 2. Content - New approach to find structure in bibliographic information – ARIADNE (2 Method) - Applications: - Data curation – author disambiguation (1 Motivation) - Illustration of topics – the case of digital humanities Topical browsing – DEMO (3) - Excursion into bibliometrics – the Berlin group challenge (4) - Wrapping up (5)
- 3. Data curation – author disambiguation
- 4. Mapping topics, communities, research fronts, ….. Bibliometrics Documents are similar because they: - Cite each other - Are cited together - Use the same references - Use the same vocabulary - Have the same authors Information retrieval Documents are similar because they: - Use the same vocabulary - - …. ARIADNE is about similarity of entities!
- 5. Document/work, Record and Entity … Authors Title Journal … Reference Subject Authors names Topical terms Reference Journal Glänzel, W. Glanzel, W. bibliometrics … … citations … Casimir effect N=SUM (doc)
- 7. Demo examples • http://thoth.pica.nl/demo/relate WorldCat • http://thoth.pica.nl/relate ArticleFirst • http://thoth.pica.nl/astro/relate Astrophysics data Berlin group
- 8. Dataset ● WorldCat, 300+ million records ● Selected 13 million items (topical terms, authors, ISSNs, Dewey decimal codes, publishers, subject headings) ● Represented by 6 million topical terms But a matrix of 13M x 6M is too big to process
- 9. C: a co-occurrence matrix R: a random matrix of +/-1 C’: approximation of C after random projection -- Semantic matrix Koopman, R., Wang, S., Scharnhorst, A., Englebienne, G.: Ariadne’s thread: In- teractive navigation in a world of networked information. In: CHI’15 Extended Abstracts. Step 1: Building the semantic matrix – and Dimension reduction based on Random Projection
- 10. Step 2: Interactive exploration - Provide a simple search/text box - Calculate the top 500 most related candidates - Find mutually related items - Convert distances to probabilities - Project to 2D - Enhance interface with links to other spaces
- 11. Exploration of a topic http://thoth.pica.nl/relate?input=hirsch%20index&fsize=100&ncluster=
- 14. EINS 1st PLENARY Digital libraries Science, Computer Science, ontologies Many different humanities fields Prominently language & Literary studies Illustration of context around a topic/field – journal view Koopman, R., Wang, S., Scharnhorst, A., Englebienne, G.: Ariadne's thread: Interactive navigation in a world of networked information. In: CHI'15 Extended Abstracts. (2015)
- 15. As visual exploration of any dataset – astrophysics case
- 16. Wrapping up – future work ● Compare the algorithm to other existing algorithms – benchmarking ● More metadata fields (publisher, subject, identifiers) – ongoing ● Identify further problems to which Ariadne can be applied ● Curation (e.g. author name disambiguation); ● Knowledge discovery (e.g. matching chemical molecules); ● Information science – population of libraries, subject areas, … ● Feedback from users – Prepare user scenarios for usability testing and set up an evaluation project – tbd ● Improve visualisation ● More functionality (timeline, history) ● Extend the implementation to other databases
- 17. Thank you rob.koopman@oclc.org shenghui.wang@oclc.org Andrea.scharnhorst@dans.knaw.nl http://thoth.pica.nl/relate (ArticleFirst) http://thoth.pica.nl/astro/relate (Astrophysics articles) http://thoth.pica.nl/demo/relate (WorldCat)
- 18. References Koopman, R., Wang, S., Scharnhorst, A., Englebienne, G.: Ariadne's thread: Interactive navigation in a world of networked information. In: B. Begole, J. Kim, K. Inkpen, W. Woo (eds.) Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems, Seoul, CHI 2015 Extended Abstracts, Republic of Korea, April 18 - 23, 2015, pp. 1833{1838. ACM (2015). DOI 10.1145/2702613.2732781. URL http://doi.acm.org/10.1145/2702613.2732781 (Preprint Arxiv.org) Koopman, R., Wang, S., Scharnhorst, A.: Contextualization of Topics - Browsing through Terms, Authors, Journals and Cluster Allocations. In: A.A. Salah, Y. Tonta, A.A.A. Salah, C. Sugimoto, U. Al (eds.) Proceedings of ISSI 2015 Istanbul. 15th International Society of Scientometrics and Informetrics Conference, Istanbul, Turkey, 29th June to 4th July 2015, pp. 1042{1053. Boazici University Printhouse, Istanbul (2015). URL http: //www.issi2015.org/en/Proceedings-of-ISSI-2015.html
Notes de l'éditeur
- [snapshot around an author as Loet Leydesdorff, Wolfgang Glaenzel] The idea at the beginning was: would one and the same author not have a similar ‘semantic’ fingerprints in s/he’s scholarly communication if we look into an article database, or book production if we look at WorldCat. The latter of course is a more complex problem, because the signal is weaker. Authors have usual less book publications than that they produce article. This network shows nodes representing author names, other words, journals … the links between them represent some similarity in terms of their lexical profile. Let me explain this in more detail.
- At the end we get document-document matrices: symmetric matrices, retrieved from asymmetric matrices such as documents-references; documents-authors; documents-words. In all those cases the unit of analysis is the document as represented by the bibliographic record – and the counterpart are elements of this record – or additional information in the document such as the references.
- In different bibliographic systems we find descriptions of works (articles, journals, objects, …) in form of a (classical) bibliographic record and often with additional information. In a first step we deconstruct the bibliographic record+ and extract categories of entities such as author names, journals names, subject headings, Dewey and other classifications. In a second step we ask how often these entities appear with topical terms. In other word, we construct now a word space not for the documents, but for the extracted entities from the document record. Documents are still relevant, because for calculating the co-occurrence of an entity and a topical term we go through all documents and count how often a certain author name and a topical word appear together. The resulting vector we call a semantic representation of an entity. Returning to our motivation: if an author is the same but spelled differently, we would assume that – in large corpus of documents, her semantic representation would be very similar. What we construct is a co-occurrence matrix between entities and topical terms. From this martix we can derive a similarity matrix between entities – taking the cosine of the vectors as measure. This similarity matrix can be visualized in form of a network, where entities are nodes and in any visual representation of this similarity the two ‘authors’ would be near to each other.
- We can of course do all this kind of analysis because we have standardized and digitized information. Ariadne has been developed around MARC records in different information servics, OCLC provides. ArticleFirst – this is were the demonstrator runs now; WorldCat – we did an exploration in this. But, in principle it can be applied to any database/set. An example you have seen in Theresa’s presentation
- If you never heard of the Hirsch Index – where does it belong to? What other terms are around it? What are the different aspects of this topic? Are there related aspects missing in my search terms? Who are the most prominent authors about this topic? Which journals publish most about this topic? How have others — e.g. librarians — described and classified this topic?
- In the case of the h-index there is a wikipedia entry which is much more detailed, still, ARIADNE gives you a first orientation
- Ariadne search into ArticleFirst a database from OCLC gives us an indication which journals are involved and based on this which fields are involved, not so surprising
- Ariadne search into ArticleFirst a database from OCLC gives us an indication which journals are involved and based on this which fields are involved, not so surprising