Sentence examples for textual corpora from inspiring English sources
Large textual corpora are available for some languages.
Argumentation mining is a recent challenge concerning the automatic extraction of arguments from unstructured textual corpora.
It also shows the fertile field for pursuing similar pedagogical projects using other authors, histories, textual corpora, or literary movements.
He develops algorithms and systems for efficient language processing, with the overall goal of synthesizing large textual corpora, such as the web, into computationally useful information.
This work is relevant for (i) knowledge engineers interested in acquiring human goals from textual corpora and constructing knowledge bases of human goals (ii) researchers interested in studying characteristics of human goals in Search Query Logs.
In order to truly gain a sufficient representation of even such a commonly used, simple concept, it is not enough to learn just from textual corpora, which has traditionally been the focus of much research in natural language processing.
This study develops an ontology building process for extracting conceptual tags and hierarchies in textual corpus.
Though humans have been creating ontologies for many years, efficient ontology building processes in textual corpus are extremely ad hoc.
Additionally, this elicitation synergy is especially useful for ontology editors who lack reference models of a working domain and who encounter textual corpus as major knowledge sources.
Our measurement, named Flickr context similarity (FCS), reflects the co-occurrence statistics of words in image context rather than the textual corpus (e.g., dictionaries or textual documents on the Web).
Basing our work on the conceptual structure of the domain under study, we will define our project and use a set of criteria that will guarantee a textual corpus that will be representative of the selected sub-field and that will subsequently facilitate the extraction of specialist terminology (Cabré, 1999; Adelstein, 2004).
