A New Tool for Textual Aggregation in OLAP Context
Overview & Synopsis
We present in this paper a system for textual aggregation from scientific documents in the online analytical processing (OLAP) context. The system extracts keywords automatically from a set of documents according to the lists compiled in the Microsoft Academia Search web site. It gives the user the possibility to choose their methods of aggregation among the implemented ones. That is TOP-Keywords, TOPIC, TUBE, TAG, BienCube and GOTA. The performance of the chosen methods, in terms of recall, precision, F-measure and runtime, is investigated with two real corpora ITINNOVATION and OHSUMED with 600 and 13,000 scientific articles respectively, other corpora can be integrated to the system by users.
Indexed from repository: HAL Open Science
(
hal.science)
Keyboard Shortcuts:
← / → for pages • + / - for zoom • 0 to fit width
Powered by Mozilla PDF.js v3.11
Document Information
| Document Title | A New Tool for Textual Aggregation in OLAP Context |
|---|---|
| Author / Organization | Mustapha Bouakkaz, Sabine Loudcher, Youcef Ouinten |
| Subject & Discipline | Multidisciplinary Academic Open Research |
| Categories | Science & Mathematics |
| Publication Year | 2016 |
| License / Rights | Open Access / Creative Commons |
| Resource Verification | Listed PDF (Verification Pending) |
| Original Host Website |
HAL Open Science
(hal.science)
|
| File Format | application/pdf (Portable Document Format) |
| Language | EN |
| Catalog ID | DOC-167737 |
| Original Source Link | Visit Source Page on hal.science » |