Titlebook: Natural Language Processing and Information Systems; 14th International C Helmut Horacek,Elisabeth Métais,Magdalena Wolska Conference proce

單挑

Semantic Approaches to Fine and Coarse-Grained Feature-Based Opinion Mininghrases related to different characteristics and the employment of Textual Entailment recognition for opinion mining. Finally, we test our approaches both on the built corpus, as well as on an ad-hoc built collection of reviews that we evaluate on the basis of the stars given. We prove that our appro

精致

prostatitis

Search Interface to a Mayan Glyph Database Based on Visual Characteristicscharacterized using a “naive” feature set. Fully working prototype is presented. Preliminary evaluation of the efficiency is carried out. In fact, the system can be applied to any set of images that can be assigned structural features.

Magisterial

exhilaration

Using Evidences Based on Natural Language to Drive the Process of Fusing Multimodal Sourcese photo task [2], jointly with the results obtained in later experiments presented in this paper show us that the use of conceptual information associated with an image can improve significantly the performance of the original multimodal fusion techniques used.

宿醉

Protein-Protein Interactions Classification from Text via Local Learning with Class Priors documents to identify abstracts containing information about protein-protein interactions with promising results. Experimental results show that LL-CP outperforms the traditional semi-supervised learning algorithms such as SVM and it also performs better than local learning without incorporating class priors.

察覺

HEED

Temporal Expression Identification Based on Semantic Rolesined in this paper. These two approaches have been evaluated using TimeBank corpus. The evaluation results confirm that the application of semantic roles to temporal expression identification task can be valuable, obtaining, for TIPSem-Full, an 73.4% in F1 for relaxed span and a 65.9% in F1 for strict span.

公社

火海

AIR: A Semi-Automatic System for Archiving Institutional Repositoriesftware adopted by many UK universities. In this paper we demonstrate that the system can considerably increase the intake of new publication data into an institutional repository without any compromise to its quality.