Zobrazeno 1 - 10
of 96
pro vyhledávání: '"Küçük, Dilek"'
Autor:
Küçük, Dilek, Can, Fazli
This tutorial aims to cover the state-of-the-art on stance detection and address open research avenues for interested researchers and practitioners. Stance detection is a recent research topic where the stance towards a given target or target set is
Externí odkaz:
http://arxiv.org/abs/2210.12383
Autor:
Küçük, Dilek
Energy research is of crucial public importance but the use of computer science technologies like automatic text processing and data management for the energy domain is still rare. Employing these technologies in the energy domain will be a significa
Externí odkaz:
http://arxiv.org/abs/2201.01559
Autor:
Küçük, Dilek
Stance detection is commonly defined as the automatic process of determining the positions of text producers, towards a target. In this paper, we define a research problem closely related to stance detection, namely, stance quantification, for the fi
Externí odkaz:
http://arxiv.org/abs/2112.13288
Autor:
Küçük, Dilek
Social media texts differ from regular texts in various aspects. One of the main differences is the common use of informal name variants instead of well-formed named entities in social media compared to regular texts. These name variants may come in
Externí odkaz:
http://arxiv.org/abs/1912.07940
Autor:
Küçük, Dilek, Can, Fazli
Annotated datasets in different domains are critical for many supervised learning-based solutions to related problems and for the evaluation of the proposed solutions. Topics in natural language processing (NLP) similarly require annotated datasets t
Externí odkaz:
http://arxiv.org/abs/1901.04787
Autor:
Küçük, Dilek, Can, Fazli
Stance detection is a subproblem of sentiment analysis where the stance of the author of a piece of natural language text for a particular target (either explicitly stated in the text or not) is explored. The stance output is usually given as Favor,
Externí odkaz:
http://arxiv.org/abs/1803.08910
Autor:
Küçük, Dilek, Küçük, Doğan
Ontologies are critical sources of semantic information for many application domains. Hence, there are ontologies proposed and utilized for domains such as medicine, chemical engineering, and electrical energy. In this paper, we present an improved a
Externí odkaz:
http://arxiv.org/abs/1803.02808
Autor:
Küçük, Dilek
Named entity recognition (NER) is a well-established task of information extraction which has been studied for decades. More recently, studies reporting NER experiments on social media texts have emerged. On the other hand, stance detection is a cons
Externí odkaz:
http://arxiv.org/abs/1707.09611
Autor:
Küçük, Dilek
Stance detection is a classification problem in natural language processing where for a text and target pair, a class result from the set {Favor, Against, Neither} is expected. It is similar to the sentiment analysis problem but instead of the sentim
Externí odkaz:
http://arxiv.org/abs/1706.06894
Autor:
Küçük, Dilek, Demirci, Turan
There is need for several software systems within the energy domain and corresponding systems are being developed to satisfy these needs. These systems include energy monitoring, information, wide area monitoring and control systems, and SCADA system
Externí odkaz:
http://arxiv.org/abs/1611.00739