Musical language does not carry obvious semantic meaning. The question of whether music has semantic meaning, or how it does, has been an age old question in musicology. This paper is a case study of musical analyses from Lawrence Kramer and Constantin Floros, and it discusses how they interpret semantic meaning into the Beethoven and Mahler pieces they analyze. Their analyses are then discussed against Nicholas Cook's model of musical meaning, and the formalist approach of Leonard B. Meyer. Even though these offer some insight to the difficulties faced in Kramer's and Floros' methods, some major problems with associating semantic meaning into music remain.

Visualisation in intelligent planning systems [Ghallab et al., 2004] is a subject that has not been given much attention by researchers. Among the existing planning systems, some well known planners do not propose a solution for visualisation at all, while others only consider a single approach when this solution sometimes is not appropriate for every situation. Thus, users cannot make the most of planning systems because they do not have appropriate support for interaction with them. This problem is more enhanced when considering mixed-initiative planning systems, where agents that are collaborating in the process have different backgrounds, are playing different roles in the process, have different capabilities and responsibilities, or are using different devices to interact and collaborate in the process. To address this problem, we propose a general framework for visualisation in planning systems that will give support for a more appropriate visualisation mechanism. This framework is divided into two main parts: a knowledge representation aspect and a reasoning mechanism for multi-modality visualisation. The knowledge representation uses the concept of ontology to organise and model complex domain problems. The reasoning mechanism gives support to reasoning about the visualisation problem based on the knowledge bases available for a realistic collaborative planning environment, including agent preferences, device features, planning information, visualisation modalities, etc. The main result of the reasoning mechanism is an appropriate visualisation modality for each specific situation, which provides a better interaction among agents (software and human) in a collaborative planning environment. The main contributions of this approach are: (1) it is a general and extensible framework for the problem of visualisation in planning systems, which enables the modelling of the domain from an information visualisation perspective; (2) it allows a tailored approach for visualisation of information in an AI collaborative planning environment; (3) its models can be used separately in other problems and domains; (4) it is based on real standards that enable easy communication and interoperability with other systems and services; and (5) it has a broad potential for its application on the Semantic Web.

There has been an increasing interest in Semantic Web services (SWS) as a proposed solution to facilitate automatic discovery, composition and deployment of existing syntactic Web services. Successful implementation and wider adoption of SWS by research and industry are, however, profoundly based on the existence of effective and easy to use methods for service semantic description. Unfortunately, Web service semantic annotation is currently performed by manual means. Manual annotation is a difficult, error-prone and time-consuming task and few approaches exist aiming to semi-automate that task. Existing approaches are difficult to use since they require ontology building. Moreover, these approaches employ ineffective matching methods and suffer from the Low Percentage Problem. The latter problem happens when a small number of service elements - in comparison to the total number of elements – are annotated in a given service. This research addresses the Web services annotation problem by developing a semi-automatic annotation approach that allows SWS developers to effectively and easily annotate their syntactic services. The proposed approach does not require application ontologies to model service semantics. Instead, a standard query template is used: This template is filled with data and semantics extracted from WSDL files in order to produce query instances. The input of the annotation approach is the WSDL file of a candidate service and a set of ontologies. The output is an annotated WSDL file. The proposed approach is composed of five phases: (1) Concept extraction; (2) concept filtering and query filling; (3) query execution; (4) results assessment; and (5) SAWSDL annotation. The query execution engine makes use of name-based and structural matching techniques. The name-based matching is carried out by CN-Match which is a novel matching method and tool that is developed and evaluated in this research. The proposed annotation approach is evaluated using a set of existing Web services and ontologies. Precision (P), Recall (R), F-Measure (F) and Percentage of annotated elements are used as evaluation metrics. The evaluation reveals that the proposed approach is effective since - in relation to manual results - accurate and almost complete annotation results are obtained. In addition, high percentage of annotated elements is achieved using the proposed approach because it makes use of effective ontology extension mechanisms.

The influence of finger-counting strategies (pointing, keep track, montring) on number representations is supported by several empirical facts. However, even the above mentioned strategies have been object of studies during childhood, little is known about how finger-counting could interact with the semantic representation of numbers in adulthood. To address this issue, we conducted a first experiment in which participants had to identify Arabic digits by pressing the keyboard with one between their ten fingers. Results showed that responses were faster and more accurate when the finger assigned to each digit was congruent with the finger-counting habits of the participants (Di Luca, Granà, Semenza, Seron and Pesenti, 2006). Subsequently, in a numerosity detection task, we showed that the numerosities expressed by canonical configurations are named faster than those expressed by non-canonical ones, even when no motors responses were needed (Di Luca and Pesenti, in press). Moreover, when used as unconsciously presented primes, both types of configurations speeded up comparative judgments of Arabic digits, but only the priming effect induced by canonical configurations generalized to new, never consciously seen, numerosities, which implies an automatic semantic access for these one only. Finally, we showed that these differences cannot be ascribed to simple visual features, but they stem from two distinct semantic processes. Specifically, canonical configurations are processed as a symbolic system and activate a place coding semantic representation of magnitude, whereas non-canonical configurations activate a summation coding semantic representation.

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