Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Berke Ozenc"'
Publikováno v:
FSMNLP
We give a FST description of nominal and finite verb morphology of Azarbaijani Turkish. We use a hybrid approach where nominal inflection is expressed as a slot-based paradigm and major parts of verb inflection are expressed as optional paths on the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::be359acd7a256309f5e211a5042d781c
https://hdl.handle.net/11729/3307
https://hdl.handle.net/11729/3307
Publikováno v:
EMNLP (Demonstration)
MorAz is an open-source morphological analyzer for Azerbaijani Turkish. The analyzer is available through both as a website for interactive exploration and as a RESTful web service for integration into a natural language processing pipeline. MorAz im
Autor:
Berke Ozenc, Ilker Cam, Gokhan Ercan, Onur Acikgoz, Burak Ertopcu, Ali Tunca Gurkan, Ozan Topsakal, Ali Bugra Kanburoglu, Olcay Taner Yildiz, Begüm Avar
Publikováno v:
2017 International Conference on Computer Science and Engineering (UBMK).
Many sentences create certain impressions on people. These impressions help the reader to have an insight about the sentence via some entities. In NLP, this process corresponds to Named Entity Recognition (NER). NLP algorithms can trace a lot of enti
Autor:
Begüm Avar, Ali Bugra Kanburoglu, Olcay Taner Yildiz, Berke Ozenc, Ozan Topsakal, Ali Tunca Gurkan, Ilker Cam, Gokhan Ercan, Burak Ertopcu, Onur Acikgoz
Publikováno v:
2017 International Conference on Computer Science and Engineering (UBMK).
Identifying the sense of a word within a context is a challenging problem and has many applications in natural language processing. This assignment problem is called word sense disambiguation(WSD). Many papers in the literature focus on English langu
Autor:
Ercan Solak, Berke Ozenc
Publikováno v:
SIU
25th Signal Processing and Communications Applications Conference (SIU) -- MAY 15-18, 2017 -- Antalya, TURKEY WOS: 000413813100439 In this study, a rule based application that collects news from public network sources and automatically tags these new
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b6ffbf3f99bac2da909f09e681251bb8
https://hdl.handle.net/11729/1725
https://hdl.handle.net/11729/1725
Autor:
Burak Ertopcu, Onur Acikgoz, Ali Tunca Gurkan, Ilker Cam, Olcay Taner Yildiz, Gokhan Ercan, Begüm Avar, Ali Bugra Kanburoglu, Ozan Topsakal, Berke Ozenc
In this study, shallow parsing is applied on Turkish sentences. These sentences are used to train and test the per-formances of various learning algorithms with various features specified for shallow parsing in Turkish. Bu çalışmada, Türkçe cüm
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::84b37f724d3316fc9b3d3f1c4fab3a32
https://hdl.handle.net/11729/1515
https://hdl.handle.net/11729/1515