Abstract
We introduce a new semantic search engine, developed at our institute. Its unique feature is the automatic construction of semantic resources, like discovery of millions of facts, IS-A relations and automated generation of sentimental analysis dictionaries. We developed a new method of document categorization. The engine can be queried in natural language and possesses interfaces to be used not only by humans but also by machines.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Ciesielski, K., Czerski, D., Dramiński, M., Kłopotek, M., Wierzchoń, S., Sydow, M., Borkowski, P., Wajda, J., Chojnicki, S., Trojanowski, K.: Semantic Resources for Enhancing Search Engines 2012, 3 Polish Academy of Sciences Annual Report 2011
Ciesielski, K., Borkowski, P., Kłopotek, M., Trojanowski, K., Wysoki, K.: Wikipedia-Based Document Categorization. LNCS, vol. 7053, pp. 265–278. Springer, New York (2012)
Dramiński, M., Owczarczyk, B., Trojanowski, K., Czerski, D., Ciesielsdki, K., Kłopotek, M.: Stabilization of Users Priofiling Proceeded by Metaclustring of Web Pages. LNCS, vol. 7912, pp. 179–186. Springer, New York (2013)
Fountain, T., Lapata, M.: Taxonomy induction using hierarchical random graphs. In: Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 466–476. Association for Computational Linguistics (2012)
Hearst, M.A.: Automatic acquisition of hyponyms from large text corpora. In: Proceedings of the 14th Conference on Computational Linguistics - Volume 2, COLING’92, Stroudsburg, pp. 539–545. Association for Computational Linguistics (1992)
Kłopotek, M.: What is the Value of Information - Search engine Point of View. LNCS, vol. 8104, pp. 1–12. Springer, New York (2013)
Kłopotek, M.A., Wierzchoń, S.T., Ciesielski, K., Dramiński, M., Czerski, D.: Ocena wartości informacji hipertekstowej. Wydawnictwo Instytut Informatyki Uniwersytetu Śląskiego Systemy Wspomagania Decyzji, pp. 227–242 (2011)
Kłopotek, M.A., Wierzchoń, S.T., Ciesielski, K., Czerski, D., Dramiński, M.: Analiza semantyczna dokumentów dla wyszukiwarek internetowych. w: Alicja Wakulicz-Deja: Systemy Wspomagania Decyzji. Instytut Informatyki Uniwersytetu Śląskiego, Katowice. pp. 135–148 (2013)
Kłopotek, M., WSierzchoń, S., Czerski, D., Ciesielski, K., Dramniński, M.: A Calculus for Personalized PageRank. LNCS, vol. 7912, pp. 212–219. Springer, New York (2013)
Kozareva, Z.: Simple, fast and accurate taxonomy learning. Text Mining, pp. 41–62. Springer International Publishing, New York (2014)
Mironczuk, M., Czerski, D., Sydow, M., Klopotek, M.: Language-independent information extraction based on formal concept analysis. In: Proceedings of Second International Conference on Informatics, Applications (ICIA), pp. 323–329 (2013). ISBN 978-1-4673-5255-0
Sydow, M., Ciesielski, K., Wajda, J.: Introducing diversity to log-based query suggestions to deal with underspecified user queries. In: Proceedings of Joint International SIIS 2011 Conference, Revised Selected Papers, vol. 7053, pp. 251–264. LNCS/Springer (2012). ISBN 978-3-642-25260-0
Szmit, R.: Locality Sensitive Hashing for Similarity Search Using MapReduce on Large Scale Data. LNCS, vol. 7912, pp. 171–178. Springer, New York (2013)
Wierzchoń, S.T., Kłopotek, M.A., Ciesielski, K., Dramiński, M., Czerski, D.: Metody obliczeniowe dla wyznaczania wektora PageRank, Wydawnictwo Instytut Informatyki Uniwersytetu Śląskiego Systemy Wspomagania Decyzji, pp. 243–252 (2011)
Wierzchoń, S., Kłopotek, M.A., Ciesielski, K.: Community detection with spectral optimization. Security, Intelligent Information Systems XVI. In: Proceedings of the International SIIS:2011
Wierzchoń, S.T., Kłopotek, M., Ciesielski, K., Czerski, D., Dramiński, M.: Accelerating PageRank computations. Control Cybern. 40(2), 377–400 (2011)
Wu, Q., Burges, C.J.C., Svore, K.M., Gao, J.: Ranking, boosting, and model adaptation. Technical report MSR-TR-2008-109, Microsoft Research (2008)
Wu, W., Li, H., Wang, H., Zhu, K.: Probase: a probabilistic taxonomy for text understanding. In: ACM International Conference on Management of Data (SIGMOD), pp. 481–492 (2012)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Czerski, D., Ciesielski, K., Dramiński, M., Kłopotek, M., Łoziński, P., Wierzchoń, S. (2016). What NEKST?—Semantic Search Engine for Polish Internet. In: Trė, G., Grzegorzewski, P., Kacprzyk, J., Owsiński, J., Penczek, W., Zadrożny, S. (eds) Challenging Problems and Solutions in Intelligent Systems. Studies in Computational Intelligence, vol 634. Springer, Cham. https://doi.org/10.1007/978-3-319-30165-5_16
Download citation
DOI: https://doi.org/10.1007/978-3-319-30165-5_16
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-30164-8
Online ISBN: 978-3-319-30165-5
eBook Packages: EngineeringEngineering (R0)