Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Liubov Kovriguina"'
Publikováno v:
IEEE Access, Vol 10, Pp 70712-70723 (2022)
SPARQL query generation from natural language questions is complex because it requires an understanding of both the question and underlying knowledge graph (KG) patterns. Most SPARQL query generation approaches are template-based, tailored to a speci
Externí odkaz:
https://doaj.org/article/faa68340dc5342f889bf9e2999cef781
Publikováno v:
Proceedings of the XXth Conference of Open Innovations Association FRUCT, Vol 420, Iss 19, Pp 332-337 (2016)
Spontaneous speech full parsing still remains an unsolved task for the Russian language although a great amount of theoretical work bas been done In the field of spontaneons speech syntax. The paper presents results on probabilistic context free gr
Externí odkaz:
https://doaj.org/article/ec7571a215a14c34b4c78ab89bce3c47
Publikováno v:
Proceedings of the XXth Conference of Open Innovations Association FRUCT, Vol 162, Iss 16, Pp 60-65 (2014)
The paper describes applying NLP algorithms to the ontology-based e-learning system. The main goal of the project is to develop a tool creating additional relations between entities based on internal analysis of object property values in the e-learni
Externí odkaz:
https://doaj.org/article/5d9b08fc9086423cb40c2bfede5ea2fe
Evaluating Natural Language Generation (NLG) systems is a challenging task. Firstly, the metric should ensure that the generated hypothesis reflects the reference's semantics. Secondly, it should consider the grammatical quality of the generated sent
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5a3af3a93d7fe8174fc955f6a59fc405
Publikováno v:
Speech and Computer ISBN: 9783319995786
SPECOM
SPECOM
The paper describes PARS - a manually annotated corpus of spoken Russian, which was built intentionally for training parsing algorithms and extracting grammars from Russian spontaneous speech. PARS corpus includes multiple annotation levels starting
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7cac650d72c921f591d1f3a4b531d85a
https://doi.org/10.1007/978-3-319-99579-3_33
https://doi.org/10.1007/978-3-319-99579-3_33
Publikováno v:
Communications in Computer and Information Science ISBN: 9783319695471
KESW
KESW
The paper concerns implementing maximum entropy tagging model and neural net dependency parser model for Russian language in Stanford CoreNLP toolkit, an extensible pipeline that provides core natural language analysis. Russian belongs to morphologic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8c3fe565755b7bc17f7e2563da9fcdd9
https://doi.org/10.1007/978-3-319-69548-8_8
https://doi.org/10.1007/978-3-319-69548-8_8
Publikováno v:
Proceedings of the XXth Conference of Open Innovations Association FRUCT, Vol 162, Iss 16, Pp 60-65 (2014)
FRUCT-16
FRUCT-16
The paper describes applying NLP algorithms to the ontology-based e-learning system. The main goal of the project is to develop a tool creating additional relations between entities based on internal analysis of object property values in the e-learni
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::94268681d33cfdca2d2e6eace450d54e
https://www.fruct.org/publications/fruct16/files/Mou.pdf
https://www.fruct.org/publications/fruct16/files/Mou.pdf
Publikováno v:
WWW (Companion Volume)
The paper concerns estimation of students' knowledge based on their learning results in the ECOLE system. ECOLE is the online eLearning system which functionality is based on several ontologies. This system allows to interlink terms from different co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::488aaa7578c37d1a141e3ef1aed00069
https://doi.org/10.1145/2740908.2741743
https://doi.org/10.1145/2740908.2741743
Publikováno v:
Semantic Web Evaluation Challenges ISBN: 9783319255170
SemWebEval@ESWC
SemWebEval@ESWC
The paper describes a number of metadata extraction procedures based on rule-based approach and pattern matching from CEUR Workshop proceedings Cf. http://ceur-ws.org and its converting to a Linked Open Data (LOD) dataset in the framework of ESWC 201
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fde05141d9330ec9f5eb21bd80327d9c
https://doi.org/10.1007/978-3-319-25518-7_13
https://doi.org/10.1007/978-3-319-25518-7_13
Publikováno v:
Semantic Web Evaluation Challenges ISBN: 9783319255170
SemWebEval@ESWC
SemWebEval@ESWC
CEUR-WS.org is a well-known place for publishing proceedings of workshops and very popular among Computer Science community. Because of that it’s an interesting source for different kinds of analytics, e.g. measurement of workshop series popularity
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4fc24adc5fdcc131a6523583948c9e06
https://doi.org/10.1007/978-3-319-25518-7_12
https://doi.org/10.1007/978-3-319-25518-7_12