Text Mining Services to Support E-Research

Abstract

In recent years the developments and opportunities created for e-Science infrastructure have promised technological support for the ever growing area of text mining applications and services. The computationally expensive tools have previously only been usable on small scale systems but are now being developed for much larger scale tasks thanks to alternative models of processing and storage. In this paper, we provide an overview of a selection of the tools available at the National Centre for Text Mining, ways they can enhance document collections, improve on traditional search techniques and how complex combinations of the tools can interact to provide advanced solutions for researchers in the UK academic community. We finish with an account of two case studies currently being investigated; examining how these processes can be extended and customised to meet the needs of domains outside the boundaries of e-Science. 1.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 3 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.