
doi: 10.1007/11669487_39
An efficient adaptive document classification and categorization approach is proposed for personal file creation corresponding to user's specific needs and profile. This kind of approach is needed because the search engines are often too general to offer a precise answer to the user request. As we cannot act directly on the search engines methodology, we propose to rather act on the documents retrieved by classifying and ranking them properly. A classifier combination approach is considered. These classifiers are chosen very complementary in order to treat all the query aspects and to present to the user at the end a readable and comprehensible result. The application performed corresponds to the law articles stemmed from the European Union data base. The law texts are always entangled with cross-references and accompanied by some updating files (for application dates, for new terms and formulations). Our approach found here a real application offering to the specialist (jurist, lawyer, etc. ) a synthetic vision of the law related to the topic requested.
[INFO.INFO-TT] Computer Science [cs]/Document and Text Processing, Document Classification File Consolidation Dynamic Classification User Profile Paploo Project
[INFO.INFO-TT] Computer Science [cs]/Document and Text Processing, Document Classification File Consolidation Dynamic Classification User Profile Paploo Project
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
