Stemming algorithms are traditionally used in Information Retrieval with the goal of enhancing recall, as they conflate the variant forms of a word into a common representation. This paper describes the development of a simple and eflective su&?x-stripping algorithm for Portuguese. The stemmer is evaluated using a method proposed by Paice f9/. The results show that it performs significantly better than the Portuguese version of the Porter algorithm.

This paper presents a system for automatically generating discourse structures from written text. The system is divided into two levels: sentence-level and text-level. The sentence-level discourse parser uses syntactic information and cue phrases to segment sentences into elementary discourse units and to generate discourse structures of sentences. At the text-level, constraints about textual adjacency and textual organization are integrated in a beam search in order to generate best discourse structures. The experiments were done with documents from the RST Discourse Treebank. It shows promising results in a reasonable search space compared to the discourse trees generated by human analysts.

Since the cell assembly (CA) was hypothesised, it has gained substantial support and is believed to be the neural basis of psychological concepts. A CA is a relatively small set of connected neurons, that through neural firing can sustain activation without stimulus from outside the CA, and is formed by learning. Extensive evidence from multiple single unit recording and other techniques provides support for the existence of CAs that have these properties, and that their neurons also spike with some degree of synchrony. Since the evidence is so broad and deep, the review concludes that CAs are all but certain. A model of CAs is introduced that is informal, but is broad enough to include, e.g. synfire chains, without including, e.g. holographic reduced representation. CAs are found in most cortical areas and in some sub-cortical areas, they are involved in psychological tasks including categorisation, short-term memory and long-term memory, and are central to other tasks including working memory. There is currently insufficient evidence to conclude that CAs are the neural basis of all concepts. A range of models have been used to simulate CA behaviour including associative memory and more process- oriented tasks such as natural language parsing. Questions involving CAs, e.g. memory persistence, CAs' complex interactions with brain waves and learning, remain unanswered. CA research involves a wide range of disciplines including biology and psychology, and this paper reviews literature directly related to the CA, providing a basis of discussion for this interdisciplinary community on this important topic. Hopefully, this discussion will lead to more formal and accurate models of CAs that are better linked to neuropsychological data.

A natural language parser implemented entirely in simulated neurons is described. It produces a semantic representation based on frames. It parses solely using simulated fatiguing Leaky Integrate and Fire neurons, that are a relatively accurate biological model that is simulated efficiently. The model works on discrete cycles that simulate 10 ms of biological time, so the parser has a simple mapping to psychological parsing time. Comparisons to human parsing studies show that the parser closely approximates this data. The parser makes use of Cell Assemblies and the semantics of lexical items is represented by overlapping hierarchical Cell Assemblies so that semantically related items share neurons. This semantic encoding is used to resolve prepositional phrase attachment ambiguities encountered during parsing. Consequently, the parser provides a neurally-based cognitive model of parsing.

Recently, there has been an increased volume of pedagogical research and practice of mobile learning (m-learning) and gameplay in education. This paper presents the findings of a study that examined the effect on achievement and explored student perception towards quiz-game play prior to an anatomy assessment in first year Higher Education students. Achievement data was collected over two academic years at all module assessment (A1-A4) points. A1 was used as a baseline, showing no difference between groups or years, A2 and A3 were comparable online assessments done on the lower and upper limbs that followed the same format; A4 was a viva-voce to assess the whole module learning. The optional 15-minute quiz-gameplay intervention (G) using a mobile application was initiated prior to A3, those students who chose not to participate performed their traditional study routine; no other changes to assessments were made resulting in a Gameplay and non-gameplay (G, NG) group for each year. Students were invited to participate in an online focus group (N = 84) and a sample undertook indepth interviews (N = 9) to gain qualitative data on their perceptions of the intervention. Students who participated in the gameplay (G) group (N = 87) demonstrated a significant improvement in A3 compared to A2, and the non-game play (NG) group (N = 164) a significant decrease. A thematic analysis was undertaken on the focus group and interview data revealing key aspects of quiz-gameplay as a learning tool. This paper offers insight into the potential benefit of encouraging m-learning gameplay as part of revision or learning for anatomy students. This information could help educators and study support facilitate efficient revision methods as well as initiate further research into the use of anatomy gameplay to enhance the student learning experience.