RSS

mayo 20, 2009
RSS is a family of web sources  formats encoded in XML. It is used to provide updated information to subscribers frequently. The format makes it possible to distribute content without a browser, using a software designed to read RSS feeds. Despite this, it is possible to use the same browser to view RSS content. The latest versions of major browsers can read RSS feeds without additional software. RSS is part of the family of XML formats developed specifically for all types of sites that are updated frequently and through which you can share information and use it on other sites or programs. This is known as re-organize  web site.
There are three types of RSS and its initials acquire a different meaning depending on the specification used:
  • Rich Site Summary. (RSS 0.91)
  • RDF Site Summary. (RSS 0.9 and 1.0)
  • Really Simple Syndication. (RSS 2.0)

 The RSS file is rewritten automatically when there is an update on the contents of the website. Accessing the RSS file is impossible to know if they have updated the content and how news texts, but without the need to access the site except to read the extended version.

 

References:

 


Project´s list (2nd questionnaire).

mayo 20, 2009

Here we have the list of projects I have chosen for this article:

1. Computational semantics. (Language technology world).

2. Language checking. (Language technology world).

3. Knowledge Discovery. (Language technology world).

4. Semantic web. (DFKI).

5. Music Information Retrieval. (DFKI).

6. Collaborating Using Diagrams. (Language Technology Group).

7. Crossmarc. (Language Technology Group).

8. Shallow Semantic Parsing. (SNLP).

9. Detecting contradictions in Text. (SNLP).

10. Document indexing for German and English. (DFKILT).

References:


Multiword expression (MWE) (Q2)

mayo 20, 2009
Multiword expression (MWE): any phrase that is not entirely predictable on the basis of standard grammar rules and lexical entries
No immediate counterexamples to the claim that any expression that can be realised hyphenated/as a single lexeme or alternatively with spaces (e.g. mailman/postman vs. mail/post man), is a MWE. This could be used in the evaluation of extraction techniques, possibly using external resources to determine whether extracted expressions can be expressed hyphenated/without spaces (e.g. determine “optimal extraction volume” as the point where the ratio of such expressions is maximised)

human language technologies (Q1)

marzo 25, 2009

          Language technology is often called human language technology (HLT) or natural language processing (NLP) and consists of computational linguistics (or CL) and speech technology as its core but includes also many application oriented aspects of them. Language technology is closely connected to computer science and general linguistics.

          It makes it easier for people to interact with machines. This can benefit a wide range of people – from illiterate farmers in remote villages who want to obtain relevant medical information over a cellphone, to scientists in state-of-the-art laboratories who want to focus on problem-solving with computers.

          The overall objective of HLT is to support e-business in a global context and to promote a human centred infostructure ensuring equal access and usage opportunities for all. This is to be achieved by developing multilingual technologies and demonstrating exemplary applications providing features and functions that are critical for the realisation of a truly user friendly Information Society. Projects address generic and applied RTD from a multi- and cross-lingual perspective, and undertake to demonstrate how language specific solutions can be transferred to and adapted for other languages.

          HLTCentral is a dedicated server providing a gateway to speech and language technology opportunities on the Web. HLTCentral web site is an online information resource of human language technologies and related topics of interest to the HLT community at large. It covers news, R&D, technological and business developments in the field of speech, language, multilinguality, automatic translation, localisation and related areas. Its coverage of HLT news and developments is worldwide – with a unique European perspective.

          The HLT Research Group studies how this technology can be applied, adapted and developed to benefit the people from southern Africa.    

          The HLT research group investigates how HLT can be adapted and applied to benefit a developing country and pursues basic and directed research relevant to the local context. This goal is considered from two perspectives:

  • HLT as an enabling technology that can play a crucial role in addressing the need for information empowerment. An example is telephone-based systems using HLT that can provide much useful information.
  • HLT as a support for language diversity in an affordable and equitable fashion. HLT can assist industry and government to make services and documents available in the 11 official languages and has a role to play in rectifying the historical discrimination against specific languages.

martin kay (Q1)

marzo 25, 2009

Martin Kay is a computer scientist known especially for his work in computational linguistics. He was responsible for introducing the notion of chart parsing in computational linguistics, and the notion of unification in linguistics generally. With Ron Kaplan, he pioneered finite-state morphology. He has been a longtime contributor to, and critic of, work on machine translation. Permanent chairman of the International Committee on Computational Linguistics, Kay was a Research Fellow at the Xerox Palo Alto Research Center until 2002. Gothenburg University has made him an honorary Filosofi Doktor.

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HANS USZKOREIT (Q1)

mayo 14, 2008

          Hans Uszkoreit is Professor of Computational Linguistics at Saarland University. At the same time he serves as Scientific Director at the German Research Center for Artificial Intelligence (DFKI) where he heads the DFKI Language Technology Lab. By cooptation he is also Professor of the Computer Science Department. 

          Uszkoreit studied Linguistics and Computer Science at the Technical University of Berlin. He co-founded the Berlin city magazine Zitty, for which he worked as an part-time editor and writer. In 1977, he received a Fulbright Grant for continuing his studies at the University of Texas at Austin. During his time in Austin he also worked as a research associate in a large machine translation project at the Linguistics Research Center.  In 1984 Uszkoreit received his Ph.D. in linguistics from the University of Texas. From 1982 until 1986, he worked as a computer scientist at the Artificial Intelligence Center of SRI International in Menlo Park, Ca. While working at SRI, he was also affiliated with the Center for the Study of Language and Information at Stanford University as a senior researcher and later as a project leader. In 1986 he spent six months in Stuttgart on an IBM Research Fellowship at the Science Division of IBM Germany. In December 1986 he returned to Stuttgart to work for IBM Germany as a project leader in the project LILOG (Linguistic and Logical Methods for the Understanding of German Texts). At the same time he also taught at the University of Stuttgart.

          In 1988 Uszkoreit was appointed to a newly created chair of Computational Linguistics at Saarland University and started the Department of Computational Linguistics and Phonetics. In 1989 he became the head of the newly founded Language Technology Lab at  DFKI. He has been a co-founder and principal investigator of the Special Collaborative Research Division (SFB 378) “Resource-Adaptive Cognitive Processes” of the DFG (German Science Foundation). He is also co-founder and professor of the “European Postgraduate Program Language Technology and Cognitive Systems”, a joint Ph.D. program with the University of Edinburgh.

          Uszkoreit is Permanent Member of the International Committee of Computational Linguistics (ICCL), Member of the European Academy of Sciences, Past President of the European Association for Logic, Language and Information, Member of the Executive Board of the European Network of Language and Speech, Member of the Board of the European Language Resources Association (ELRA), and serves on several international editorial and advisory boards.  He is co-founder and Board Member of XtraMind Technologies GmbH, Saarbruecken, acrolinx gmbh, Berlin and Yocoy Technologies GmbH, Berlin. Since 2006, he serves as Chairman of the Board of Directors of the international initiative dropping knowledge.

          His current research interests are computer models of natural language understanding and production, advanced applications of language and knowledge technologies such as semantic information systems, translingual technologies, cognitive foundations of language and knowledge, deep linguistic processing of natural language, syntax and semantics of natural language and the grammar of German.


The Stanford NLP Group (Q2)

mayo 14, 2008

          The Natural Language Processing Group at Stanford University is a team of faculty, postdocs, and students who work together on algorithms that allow computers to process and understand human languages. Our work ranges from basic research in computational linguistics to key applications in human language technology, and covers areas such as sentence understanding, probabilistic parsing and tagging, biomedical information extraction, grammar induction, word sense disambiguation, and automatic question answering.

          A distinguishing feature of the Stanford NLP Group is our effective combination of sophisticated and deep linguistic modeling and data analysis with innovative probabilistic and machine learning approaches to NLP. Our research has resulted in state-of-the-art technology for robust, broad-coverage natural-language processing in many languages. These technologies include our part-of-speech tagger, which currently has the best published performance in the world; a high performance probabilistic parser; a competition-winning biological named entity recognition system; and algorithms for processing Arabic, Chinese, and German text.

          The Stanford NLP Group includes members of both the Linguistics Department and the Computer Science Department, and is affiliated with the Stanford AI Lab and the Stanford InfoLab.