Marlo Souza

Sentiment analysis on twitter data for portuguese language

This work presents an study on Sentiment Analysis on Twitter data for the Portuguese language. It evaluates the impact of different preprocessing techniques, Portuguese polarity lexicons and negation models showing low impact of preprocessing and negation modelling in classification of tweets.

PIRPO: An Algorithm to Deal with Polarity in Portuguese Online Reviews from the Accommodation Sector

This paper presents the algorithm Polarity Recognizer in Portuguese (PIRPO) to classify sentiment in online reviews. PIRPO was constructed to identify polarity in Portuguese user generated accommodation reviews. Each review is analysed according to concepts from a domain ontology. We decompose the review in sentences in order to assign a polarity to each concept of the ontology in the sentence. Preliminary results indicate an average F-score of 0.32 for polarity recognition.

Open information extraction based on lexical semantics

BackgroundOpen Information Extraction (Open IE) aims to obtain not predefined, domain-independent relations from text. This article introduces the Open IE research field, thoroughly discussing the main ideas and systems in the area as well as its main challenges and open issues. The paper describes an open extractor elaborated from the belief that it is not necessary to have an enormous list of patterns or several types of linguistic labels to better perform Open IE. The extractor is based on generic patterns that identify relations not previously specified, including rules corresponding to Cimiano and Wenderoth proposal to learn Qualia structure.MethodsNamed LSOE (Lexical-Syntactic pattern-based Open Extractor) and designed to validate such strategy, this extractor is presented and its performance is compared with two Open IE systems.ResultsThe results demonstrate that LSOE extracts relations that are not learned by other extractors and achieves compatible precision.ConclusionsThe work reported here contributes with a new Open IE approach based on pattern matching, demonstrating the feasibility of an extractor based on simple lexical-syntactic patterns.

Open Information Extraction Based on Lexical-Syntactic Patterns

Open Information Extraction (Open IE) is an unsupervised strategy to draw out relations from text without predefining these relations, regardless the domain. This paper describes a novel Open IE approach that performs unsupervised extraction of triples by applying a few lexical-syntactic patterns to POS-tagged texts. In order to validate this strategy we developed a prototype and compared its performance with two Open IE systems. The proposed approach achieved promising results, overcoming those from the state-of-the-art systems. The paper concludes with an analysis of errors and directions for future work.

Communication for Agents with Ontological Reasoning

Communication in heterogeneous Multi-Agent Systems is an active area of study in Computer Science. As far as it has been achieved in the last few years, however, to our knowledge there is still little work on integrating ontology-based communication in the semantics of agent programming languages. In this work, we study communication between agents with underlying ontological reasoning. The resulting communication mechanism allows agents to exchange not only factual but also terminological knowledge about an individual domain.

Integrating Ontology Negotiation and Agent Communication

Ontologies are considered a necessary ingredient for communication among heterogeneous agents in the Web. With the multiplication of ontologies for the same domains, semantic interoperability has become a challenge. In this work, we study the use of ontology negotiation in a agent communication mechanism for agents with ontological reasoning. The resulting communication mechanism allows agents to exchange not only factual but also terminological knowledge about an individual domain and is closely related to available mechanisms in the literature such as KQML and FIPA-ACL.