Enhancing Information Accessibility of Publications with Text Mining and Ontology

The first tool identifies numeric properties in the patent text and normalises them, the second extracts a list of keywords that are relevant and reveal the invention in the patent

That way, a plethora of text analytics and NLP tasks (e.g., web search, text categorization and keyword extraction), have been addressed combining a graph-based representation of

We intend to identify verbal terminological collocations (VTC) whose base is the verb “escolher” or “separar” followed by a specialised term used in the domain under analysis, and

The first three columns de- note whether time abstraction on both vertices and edges is used, whether the patterns were used to score sentences, and whether the initial weights

Nev- ertheless, Big Data technologies and massive clustering techniques are now possible so that the release of a TREC style collection, that is still missing, will help the IR and

In response to the above, text mining (TM) aims to automate the above process, by finding relations (such as interactions) that hold between concepts of different types

Abstract— Genomic profiling information is frequently available to oncologists, enabling targeted cancer therapy. Because clinically relevant genomic information is rapidly

iPTMnet integrates text mining results from RLIMS-P and eFIP that have been automatically normalized (i.e., the proteins detected in text have been mapped to their