Seeking Relevant Information Sources

@inproceedings{44022,
   author = {Menšík, Marek and Duží, Marie and Albert, Adam and Patshka, Vojtěch and Pajr, Miroslav},
   address = {Montreal, Canada},
   booktitle = {2019 IEEE 15th International Scientific Conference on Informatics},
   doi = {http://dx.doi.org/10.1109/Informatics47936.2019.9119332},
   keywords = {Information sources; Machine learning; TIL},
   howpublished = {elektronická verze "online"},
   language = {eng},
   location = {Montreal, Canada},
   isbn = {978-1-7281-3181-8},
   pages = {255-260},
   publisher = {Institute of Electrical and Electronics Engineers},
   title = {Seeking Relevant Information Sources},
   url = {https://ieeexplore.ieee.org/document/9119332},
   year = {2019}
}

TY  - JOUR
ID  - 44022
AU  - Menšík, Marek - Duží, Marie - Albert, Adam - Patshka, Vojtěch - Pajr, Miroslav
PY  - 2019
TI  - Seeking Relevant Information Sources
PB  - Institute of Electrical and Electronics Engineers
CY  - Montreal, Canada
SN  - 9781728131818
KW  - Information sources
KW  - Machine learning
KW  - TIL
UR  - https://ieeexplore.ieee.org/document/9119332
L2  - https://ieeexplore.ieee.org/document/9119332
N2  - In this paper we deal with the problem of seeking relevant information sources selected from scientific or other electronic publications. In the era of information surfeit, it is getting more and more difficult to extract relevant and reliable sources of information from the huge number of e-sources. The starting point is user's query for a given concept or topic. Our algorithm applies machine learning methods in order to propose hypothetic explications of the sought terms based on pieces of information extracted from the potentially relevant e-sources. Hypotheses, formalized in the TIL-Script language, are incrementally built by applying heuristic functions. The user thus obtains as closed approximations of the meaning of the sought terms as possible that at the same time provide fine-grained keyword definitions. As a result, it should be much easier to decide which of the e-sources are relevant for user's interest.
ER  - 

MENŠÍK, Marek, Marie DUŽÍ, Adam ALBERT, Vojtěch PATSHKA and Miroslav PAJR. Seeking Relevant Information Sources. Online. In \textit{2019 IEEE 15th International Scientific Conference on Informatics}. Montreal, Canada: Institute of Electrical and Electronics Engineers, 2019, p.~255-260. ISBN~978-1-7281-3181-8. Available from: https://dx.doi.org/10.1109/Informatics47936.2019.9119332.