Zobrazeno 1 - 10
of 196
pro vyhledávání: '"Aker, Ahmet"'
Publikováno v:
In CHIIR '21: Proceedings of the 2021 Conference on Human Information Interaction and Retrieval
Shopping online is more and more frequent in our everyday life. For e-commerce search systems, understanding natural language coming through voice assistants, chatbots or from conversational search is an essential ability to understand what the user
Externí odkaz:
http://arxiv.org/abs/2302.06355
Search systems on the Web rely on user input to generate relevant results. Since early information retrieval systems, users are trained to issue keyword searches and adapt to the language of the system. Recent research has shown that users often with
Externí odkaz:
http://arxiv.org/abs/2302.06349
The spreading COVID-19 misinformation over social media already draws the attention of many researchers. According to Google Scholar, about 26000 COVID-19 related misinformation studies have been published to date. Most of these studies focusing on 1
Externí odkaz:
http://arxiv.org/abs/2106.11702
Publikováno v:
Proceedings of the 2020 ACM on Designing Interactive Systems Conference, 2020, pp. 2077-2089
With the rise of voice assistants and an increase in mobile search usage, natural language has become an important query language. So far, most of the current systems are not able to process these queries because of the vagueness and ambiguity in nat
Externí odkaz:
http://arxiv.org/abs/2008.02114
Autor:
Kowollik, Jan, Aker, Ahmet
In this paper we present our system for the FEVER Challenge. The task of this challenge is to verify claims by extracting information from Wikipedia. Our system has two parts. In the first part it performs a search for candidate sentences by treating
Externí odkaz:
http://arxiv.org/abs/1812.10814
Publikováno v:
In RANLP 2017
Stance classification determines the attitude, or stance, in a (typically short) text. The task has powerful applications, such as the detection of fake news or the automatic extraction of attitudes toward entities or events in the media. This paper
Externí odkaz:
http://arxiv.org/abs/1708.05286
Debate summarization is one of the novel and challenging research areas in automatic text summarization which has been largely unexplored. In this paper, we develop a debate summarization pipeline to summarize key topics which are discussed or argued
Externí odkaz:
http://arxiv.org/abs/1708.04587
Usage of online textual media is steadily increasing. Daily, more and more news stories, blog posts and scientific articles are added to the online volumes. These are all freely accessible and have been employed extensively in multiple research areas
Externí odkaz:
http://arxiv.org/abs/1708.04592
Publikováno v:
ACM Computing Surveys 51, 2, Article 32 (February 2018), 36 pages
Despite the increasing use of social media platforms for information and news gathering, its unmoderated nature often leads to the emergence and spread of rumours, i.e. pieces of information that are unverified at the time of posting. At the same tim
Externí odkaz:
http://arxiv.org/abs/1704.00656
Autor:
Eser, Erhan, Cil, Elif, Sen Gundogan, Nesibe Efruz, Col, Meltem, Yildirim Ozturk, Elif Nur, Thomas, David Terence, Sunter, Ahmet Tevfik, Arslan, Hatice Nilden, Citil, Riza, Onder, Yalcin, Picakciefe, Metin, Dede, Bahadir, Demirel, Can, Aydin, Neriman, Caglayan, Cigdem, Aker, Ahmet Alp, Borlu, Arda, Durmus, Hasan, Can, Gunay, Siddikoglu, Esin
Publikováno v:
Teaching & Learning in Medicine; Oct-Dec2024, Vol. 36 Issue 5, p588-600, 13p
