Information Extraction (IE) aims at mapping texts into fixed structure representing the key information. A typical IE system will try to answer the questions like who are present in the text, what events happen and when these events happen. The task is making possible significant advances in applications that require deep understanding capabilities such as questionanswering engines, dialogue sy...

In this paper we present a truly semantic-oriented approach for meronymy relation extraction. It directly operates, instead of syntactic trees or surface representations, on semantic networks (SNs). These SNs are derived from texts (in our case, the German Wikipedia) by a deep linguistic syntactico-se mantic analysis. The extraction of meronym/holonym pairs is carried out by using, among other...

The fields of Digital Humanities and Digital Preservation are not yet enjoying the full potential of the Semantic Web and relevant technologies, largely due to the highly contextualized nature of their source materials. This paper addresses the issue of representing context and use-context (i.e. context of use) of digital content, by proposing an ontology-based representation approach, which is...

Ontology generation—a process to automatically create ontologies from existing knowledge sources—has become a key issue with the emergence of the semantic web. Though many researchers are trying to automate this process by exploiting machine learning and data mining techniques, the results remain under exploration. At the same time, when more and more ontologies are available online, it is impo...

In this paper, we construct a biomedical semantic role labeling (SRL) system that can be used to facilitate relation extraction. First, we construct a proposition bank on top of the popular biomedical GENIA treebank following the PropBank annotation scheme. We only annotate the predicate-argument structures (PAS’s) of thirty frequently used biomedical predicates and their corresponding argument...

Many NLP tasks make predictions that are inherently coupled to syntactic relations, but for many languages the resources required to provide such syntactic annotations are unavailable. For others it is unclear exactly how much of the syntactic annotations can be effectively leveraged with current models, and what structures in the syntactic trees are most relevant to the current task. We propos...

DBpedia is a Semantic Web project aiming to extract structured data from Wikipedia articles. Due to the increasing number of resources linked to it, DBpedia plays a central role in the Linked Open Data community. Currently, the information contained in DBpedia is mainly collected from Wikipedia infoboxes, a set of subject-attribute-value triples that represents a summary of the Wikipedia page. ...

To cover promising research topics, TKDE has kept a tradition of organizing and publishing special issues in a timely manner. We published a special issue on Mining Biological Data in the August 2005 issue, and another special issue on Intelligent Data Preparation in the September 2005 issue. Meanwhile, to maintain the health of TKDE's current publication queue and to avoid negative impact on t...

Chinese entity relation extraction is a part of entity relation extraction. According to entity relation extraction technology and the features of Chinese news corpus, this paper proposes a novel method for Chinese entities relation extraction. The method, named WCORE (word co-occurrence relation extraction), first measures the semantic similarity by word co-occurrence and then adopts pattern m...

Automatic evaluation of GOR (Goodness Of pRosody) is a more advanced and challenging task in CALL (Computer Aided Language Learning) system. Apart from traditional prosodic features, we develop a method based on multiple knowledge sources without any prior condition of reading text. After speech recognition, apart from most state-of-the-art features in prosodic analysis, we cultivate more conci...