Abstract
With the growing popularity of research in Temporal Information Retrieval (T-IR), a large amount of temporal data is ready to be exploited. The ability to exploit this information can be potentially useful for several tasks. For example, when querying "Football World Cup Germany", it would be interesting to have two separate clusters {1974,2006} corresponding to each of the two temporal instances. However, clustering of search results by time is a non-trivial task that involves determining the most relevant dates associated to a query. In this paper, we propose a first approach to flat temporal clustering of search results. We rely on a second order co-occurrence similarity measure approach which first identifies top relevant dates. Documents are grouped at the year level, forming the temporal instances of the query. Experimental tests were performed using real-world text queries. We used several measures for evaluating the performance of the system and compared our approach with Carrot Web-snippet clustering engine. Both experiments were complemented with a user survey.

Abstract
It is well established that S-shaped curves describe the diffusion processes of many innovations quite well, but little insight on the mechanics of diffusion is achieved by simple curve fitting. We propose an evolutionary model of the diffusion process, focusing on the characteristics of economic agents and on the interactions among them, and relate those determinants with the observed shape of the diffusion curve. Using simulation techniques, we show that the proposed model is able to explain why an innovation may not diffuse globally across an economy/region, even when it faces no rival innovations. Moreover, we show how network size, informational spillovers, and the behavior of innovation prices shape the diffusion process. The results regarding network size and informational spillovers rationalize the importance of informational lock-outs, proving they can influence both the aggregate adoption rate and the speed of the diffusion process. With respect to innovation prices, simulation results show that faster price decline leads to higher aggregate adoption rates, and that the diffusion process is more sensitive to the pricing dynamics than to the network size or the behavior of spillovers.

Abstract
Multi-agent systems paradigm is a suitable approach to implement distributed manufacturing systems addressing the emergent requirements of flexibility, robustness and responsiveness. In such systems, an ontology is a crucial piece to provide a common understanding on the vocabulary used by the intelligent, distributed agents during the exchange of shared knowledge. This paper describes the design of an ontology to define the structure of the knowledge that is used within a multi-agent system integrating process and quality control in production lines for home appliances, which is being developed within the EU FP7 GRACE (inteGration of pRocess and quAlity Control using multi-agEnt technology) project. The ontology schema is validated by instantiating for a case study derived from a washing machines production line.

Abstract
The large amount of pages in Websites is a problem for users who waste time looking for the information they really want. Knowledge about users' previous visits may provide patterns that allow the customization of the Website. This concept is known as Adaptive Website: a Website that adapts itself for the purpose of improving the user's experience. Some Web Mining algorithms have been proposed for adapting a Website. In this paper, a recommender system using agents with two different algorithms (associative rules and collaborative filtering) is described. Both algorithms are incremental and work with binary data. Results show that this multi-agent approach combining different algorithms is capable of improving user's satisfaction.

Abstract
Very few studies on the assessment and evolution of Chinese economics research draw on quantitative methods, namely bibliometrics. Bibliometrics is a powerful tool that helps to explore, organize and analyze large amounts of information in a quantitative manner. Selecting the most important economic journal focusing on the Chinese economy - the China Economic Review (CER) - we classified and assessed all the (512) articles that have been published in CER from its founding (1989) to December 2010. Based on these articles, and undertaking an exploratory statistical analysis on three databases - a 'bibliographic' database (512 articles), a 'roots' database (over 10 thousand citations), and an 'influence' database (over 3 thousand citations), we concluded that: 1) 'Economic Development, Technological Change, and Growth': 'Economic Systems', and 'International economics' are the most important topics for Chinese economics literature; 2) there is a trend in Chinese economics research for growing 'rigor', associated to a noticeable rise in the weight of formal/mathematical-based articles; 3) the 'International economics' topic does not influence nor is it influenced by Chinese economics literature; and 4) Chinese economics literature is characterized by a certain level of endogamy, given that its range of influence is rather concentrated (geographically) in China and the USA.

Abstract
An interferometer based on a D-shape chaotic optical fiber for measurement of multiparameters was proposed. The sensing structure relied on a D-shape fiber section spliced in between two singlemode fibers and interrogated in transmission. The optical spectrum was composed by multiple interference loss peaks, which were sensitive to the refractive index, temperature and strain-maximum sensitivities of 95.2 nm/RIU, 10.5 pm/ and -3.51 pm/µe, respectively, could be achieved. © The Author(s) 2012.