Autor: Beatriz Botella
The Effect of Various Straightforward Summarization Techniques on Informativeness of Abstractive Summaries
In the present paper we describe how a straight forward abstractive text summarization method based on syntactic text simplification, subject-verb-object concept frequency scoring and a set of rules that transform […]
Towards Adapting Automatic Text Summarization for L2 Learners: Does Compression Rate Affect Summary Readability?
This paper addresses the problem of readability of automatically generated summaries in the context of second language learning. For this we experimented with a new corpus of level-annotated simplified English […]
Tackling the Challenge of Computational Identification of Characters in Fictional Narratives
This paper focuses on the computational identification of characters in fictional narratives, regardless of their nature, i.e., either humans, animals or other type of beings. We approach this problem as […]
NATSUM: Narrative abstractive summarization through cross-document timeline generation
A new approach to narrative abstractive summarization (NATSUM) is presented in this paper. NATSUM is centered on generating a narrative chronologically ordered summary about a target entity from several news […]
Distributed Architectures for Intensive Urban Computing: A Case Study on Smart Lighting for Sustainable Cities
New information and communication technologies have contributed to the development of the smart city concept. On a physical level, this paradigm is characterized by deploying a substantial number of different […]
A Review of the Analytics Techniques for an Efficient Management of Online Forums: An Architecture Proposal
E-learning is a response to the new educational needs of society and an important development in information and communication technologies because it represents the future of the teaching and learning […]
MergedTrie: Efficient textual indexing
The accessing and processing of textual information (i.e. the storing and querying of a set of strings) is especially important for many current applications (e.g. information retrieval and social networks), […]
GPLSI at TREC 2018 RTS Track
In this paper we present our contribution for the TREC 2018 Real-Time Summarization track. This task contains two scenarios: push notifications, and email digest. We participated in both, submitting three […]
AutoML strategy based on grammatical evolution: A case study about knowledge discovery from text
The process of extracting knowledge from natural language text poses a complex problem that requires both a combination of machine learning techniques and proper feature selection. Recent advances in Automatic […]
A General-Purpose Annotation Model for Knowledge Discovery: Case Study in Spanish Clinical Text
Knowledge discovery from text in natural language is a task usually aided by the manual construction of annotated corpora. Specifically in the clinical domain, several annotation models are used depending […]