Tag-Archive for » mena badieh habib «

Thursday, May 15th, 2014 | Author:

Tweakers.net, NU.nl and Kennislink.nl picked up the UT homepage news item on the research of my PhD student Mena Badieh Habib on Named Entity Extraction and Named Entity Disambiguation.
Tweakers.net: UT laat politiecomputers tweets ‘begrijpen’ voor veiligheid bij evenementen
NU.nl: Universiteit Twente laat computers beter begrijpend lezen
Kennislink.nl: Twentse computer leest beter

Wednesday, May 14th, 2014 | Author:

The news feed of the UT homepage features an item on the research of my PhD student Mena Badieh Habib.
Computers leren beter begrijpend lezen dankzij UT-onderzoek (in Dutch).
Mena defended his PhD thesis entitled “Named Entity Extraction and Disambiguation for Informal Text – The Missing Links on May 9th.

Friday, May 09th, 2014 | Author:

Today, a PhD student of mine, Mena Badieh Habib Morgan, defended his thesis.
Named Entity Extraction and Disambiguation for Informal Text – The Missing Link
Social media content represents a large portion of all textual content appearing on the Internet. These streams of user generated content (UGC) provide an opportunity and challenge for media analysts to analyze huge amount of new data and use them to infer and reason with new information. A main challenge of natural language is its ambiguity and vagueness. When we move to informal language widely used in social media, the language becomes even more ambiguous and thus more challenging for automatic understanding. Named Entity Extraction (NEE) is a sub task of Information Extraction (IE) that aims to locate phrases (mentions) in the text that represent names of entities such as persons, organizations or locations regardless of their type. Named Entity Disambiguation (NED) is the task of determining which correct person, place, event, etc. is referred to by a mention. The main goal of this thesis is to mimic the human way of recognition and disambiguation of named entities especially for domains that lack formal sentence structure. We propose a robust combined framework for NEE and NED in semi-formal and informal text. The achieved robustness has been proven to be valid across languages and domains and to be independent of the selected extraction and disambiguation techniques. It is also shown to be robust against shortness in labeled training data and against the informality of the used language.

Monday, April 07th, 2014 | Author:

Last year we won the #Microposts2013 challenge; this year we came in second for the new #Microposts2014 challenge called NEEL, “Named Entity Extraction and Linking”, that as opposed to last year also involves Entity Disambiguation (by linking to DBpedia).
Named Entity Extraction and Linking Challenge: University of Twente at #Microposts2014 [Download]
Mena Badieh Habib, Maurice van Keulen, Zhemin Zhu

Monday, May 13th, 2013 | Author:

Together with my PhD student Mena Badieh Habib and another PhD student of our group Zhemin Zhu, we participated in the “Making Sense of Microposts” challenge at the WWW 2013 conference … and we won the best IE award!
[paper | presentation | poster]

Friday, December 02nd, 2011 | Author:

One of my PhD students, Mena Badieh Habib, has given a talk on the Dutch-Belgian DataBase Day (DBDBD) about “Named Entity Extraction and Disambiguation from an Uncertainty Perspective“.

Monday, August 22nd, 2011 | Author:

One of my PhD students, Mena Badieh Habib, and I submitted a paper about improving the effectiveness of named entity extraction (NEE) with what we call “the reinforcement effect” to the MUD workshop of VLDB2011.
Named Entity Extraction and Disambiguation: The Reinforcement Effect.
Mena Badieh Habib, Maurice van Keulen
Named entity extraction and disambiguation have received much attention in recent years. Typical fields addressing these topics are information retrieval, natural language processing, and semantic web. Although these topics are highly dependent, almost no existing works examine this dependency. It is the aim of this paper to examine the dependency and show how one affects the other, and vice versa. We conducted experiments with a set of descriptions of holiday homes with the aim to extract and disambiguate toponyms as a representative example of named entities. We experimented with three approaches for disambiguation with the purpose to infer the country of the holiday home. We examined how the effectiveness of extraction influences the effectiveness of disambiguation, and reciprocally, how filtering out ambiguous names (an activity that depends on the disambiguation process) improves the effectiveness of extraction. Since this, in turn, may improve the effectiveness of disambiguation again, it shows that extraction and disambiguation may reinforce each other.

The paper will be presented at the MUD workshop co-located with VLDB 2011, 29 August 2011, Seattle, USA [details]

Wednesday, December 22nd, 2010 | Author:

One of my PhD students, Mena Badieh Habib, submitted a paper with his research plans in the Neogeography project to the PhD workshop of ICDE2011.
Neogeography: The Challenge of Channelling Large and Ill-Behaved Data Streams
Mena Badieh Habib
Neogeography is the combination of user generated data and experiences with mapping technologies. In this paper we propose a research project to extract valuable structured information with a geographic component from unstructured user generated text in wikis, forums, or SMSes. The project intends to help workers communities in developing countries to share their knowledge, providing a simple and cheap way to contribute and get benefit using the available communication technology.

The paper will be presented at the PhD workshop co-located with ICDE 2010, 11 April 2011, Hannover, Germany [details]