Edgar Gonzàlez, que va fer la tesis al centre, apareix al diari la Vanguardia com a exemple del selecte grup de talents que s'han instal·lat a la costa oest d'Estats Units per poder fer carrera en el sector tecnològic.

Title

Probabilistic Inference for Weakly-Supervised Entity-Relation
and
Learning Word Embeddings for Language Modelling

Speaker
Audi Primadhanty and Pranava Swaroop Madhyastha

Room
Omega-S208 Campus Nord - UPC

Date
Fri Feb 07, 2014

Time
12:00h - 14:00h

Abstract for Probabilistic Inference for Weakly-Supervised Entity-Relation

We investigate the task of extracting entities and relations from text documents given only a few examples of desired entities and relations. The task is relevant for information extraction in new, open domains where the availability of annotated corpus is negligible or expensive to obtain. We begin with the task of named entity classification by proposing a probabilistic generative model that uses hidden states. the purpose of hidden states is to capture commonalities of the contexts in which entities of different types appear. Our hope is that this model will have improved robustness when it comes to recognize unseen entities. Our aim is to further extend such techniques for extracting relations in any domain for specific target entities and relations in a large unlabeled corpus, requiring only few examples for each entity and relation type.  

Abstract for Learning Word Embeddings for Language Modelling

Title
Using Frames to converting texts to ontologies. Solutions can be combined?

Speaker
Alma Delia Cuevas (CIC-IPN and UAEM) México

Room
Omega-S208 Campus Nord - UPC

Date
Wed Nov 27, 2013

Time
11:00h

Abstract

To automatically extract knowledge from natural language documents is an interesting chore, since it obtains information in a simple manner, without the need of human interpretation, which often consumes large amounts of time. But for a computer to “understand” a document is a non-trivial task, since natural language is ambiguous, full of synonyms, idioms, anaphora, word declinations, analogies… which persons solve not only through context, but also with previous knowledge, real world experience and common sense. None of these are salient features of a computer.

To obtain knowledge automatically from any text (prose, poetry, news, event descriptions, text books, cooking recipes, descriptive documents, etc.) and to be able to transform it to a representation which a computer can understand and process, is still far from reality. Nevertheless, progress in this acquisition is performed with the use of natural language processing (NLP), information retrieval and knowledge acquisition tools.

Aware of the problem of trying to interpret all types of text, the scope of SERCDD (System for Extracting and Representing Knowledge from Descriptive Documents) is descriptive texts: documents describing tools, plants, geographic places, etc.

Title
The architecture of the Asiya Web Service

Speaker
Meritxell Gonzàlez

Room
Omega-S208 Campus Nord - UPC

Date
Tue Nov 19, 2013

Time
11:00h

Abstract

Asiya is an MT evaluation tool that uses a number of parsers and other language analyzers. Processing a complete testbed is resource intensive (in terms of time, CPU and memory), which is problematic, mainly for two reasons: it overloads the server, and online users suffer from server timeouts. The solution adopted is a web service that submits a job to the cluster. In this seminar, I will explain the details of this architecture.

Slides