Nearly every practical improvement in modeling human motion is well founded in a properly designed collection of data or datasets. These datasets must be made publicly available for the community could validate and accept them. It is reasonable to concede that a collective, guided enterprise could serve to devise solid and substantial datasets, as a result of a collaborative effort, in the same sense as the open software community does. In this way datasets could be complemented, extended and expanded in size with, for example, more individuals, samples and human actions. For this to be possible some commitments must be made by the collaborators, being one of them sharing the same data acquisition platform. In this paper, we offer an affordable open source hardware and software platform based on inertial wearable sensors in a way that several groups could cooperate in the construction of datasets through common software suitable for collaboration. Some experimental results about the throughput of the overall system are reported showing the feasibility of acquiring data from up to 6 sensors with a sampling frequency no less than 118Hz. Also, a proof-of-concept dataset is provided comprising sampled data from 12 subjects suitable for gait analysis.

The geographic scope of Web pages is becoming an essential dimension of Web search, especially for mobile users. This paper shows a multistage method for assigning a geographic focus to Web pages (GeoReferencing) according to their text contents. We suggest several heuristics for the disambiguation toponyms and a scoring procedure for focus determination. Furthermore, we provide an experimental methodology for evaluating the accuracy. Finally, we obtained promising results of over 70% accuracy with a city-level resolution.

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Many document collections contain documents that have significant structure. Structured document retrieval requires different models and interfaces from standard Information Retrieval. An Information Retrieval system dealing with structured documents has to enable a user to query, browse retrieved documents, and provide query refinement and relevance feedback based not only on full documents but also on specific parts of them, according to their structure. Currently, very few IR systems enable such level of flexibility and interaction, because of limitations in indexing and retrieval models and in interfaces. In this paper, we present the design of a new graphical user interface for structured document retrieval. This interface provides the user with an intuitive and yet powerful set of tools for structured document searching, retrieved list navigation, and search refinement. 1

We present a new model to query document databases by content and structure. The main merits of the model are: it allows rich structure in the documents; the query algebra is intuitive (moreover, complemented by a visual query language) and powerful; it is efficiently implementable; it can be built on top of a traditional indexing system or even with no index at all; it is strongly oriented to user-definable relevance ranking instead of boolean logic; and it allows flexible visualization of results in terms of structure, contents and highlighting of user-defined important parts in the query.