Metapolitefsi: From the Transition to Democracy to the Economic Crisis, Athens, 14–16 December 2012

The conference on “Metapolitefsi: From the Transition to Democracy to the Economic Crisis”, organised by Historein in collaboration with the Free University of Berlin and held in Athens on 14–16 December 2012, sought to offer a first systematic account of the historical period from the fall of the Greek military dictatorship (1974) to the recent economic crisis. This postauthoritarian period in Greek politics and society is frequently referred to as the metapolitefsi

Incorporate Cultural Artifacts Conservation Documentation to Information Exchange Standards – The DOC-CULTURE Case

AbstractThe cultural heritage artifacts Conservation Documentation format is not universally agreed upon nor has it always been considered an important aspect of the conservation profession. Conservation records present major drawbacks, which are the fragmentary and incomplete description of the contained information and related processes. On the other hand, as strict regulations prohibit invasive testing in the conservation of art works and monuments of great historical value, new type of examination methods such as Non-Destructive Testing and Evaluation (NDT&E) techniques have become essential and are widely used by scientists. In this context, the present paper presents the DOC-CULTURE project approach to standardize the documentation of the NDT methods and their output data through CIDOC-CRM exploitation

Self-other agreement for improving communication in libraries and information services

Purpose – This paper aims to examine the Self-Other Agreement between leaders and employees in the sector of Libraries and Information Services (LIS) to construct a sustainable and strategic communicational process among library directors and staff. Design/methodology/approach – A sample of 135 leaders-employees of 17 organisations of LIS in more than five countries answered on a quantitative methodological research instrument in a multiplicity of variables. Statistical analysis of independent samples t-test was used to testify our research hypotheses. Findings – Results indicated that there is a difference in means between the two independent samples (leaders-employees). There are library leaders who rate themselves quite high, and there are employees who rate their leaders with lower evaluations. Research limitations/implications – This research extends and improves the matter of Self-Other Agreement in the sector of LIS through the collection of data that indicated a possible gap of communication and trustworthiness between leaders and employees. Practical implications – Regardless of the difference or the consensus of ratings among leaders and employees, the results of this research could be served as a stimulus plus as a starting point for library leaders by correcting or developing relations of communication and trustworthiness between them and their followers. Originality/value – Self-Other Agreement is one of the major factors that positively or negatively affect the overall operation of the organization in the way a leader could perceive the additional feedback. In the sector of LIS, the study of Self-Other Agreement is a rich and unexplored research area which deserves further analysis

Tree-based Focused Web Crawling with Reinforcement Learning

A focused crawler aims at discovering as many web pages relevant to a target topic as possible, while avoiding irrelevant ones. Reinforcement Learning (RL) has been utilized to optimize focused crawling. In this paper, we propose TRES, an RL-empowered framework for focused crawling. We model the crawling environment as a Markov Decision Process, which the RL agent aims at solving by determining a good crawling strategy. Starting from a few human provided keywords and a small text corpus, that are expected to be relevant to the target topic, TRES follows a keyword set expansion procedure, which guides crawling, and trains a classifier that constitutes the reward function. To avoid a computationally infeasible brute force method for selecting a best action, we propose Tree-Frontier, a decision-tree-based algorithm that adaptively discretizes the large state and action spaces and finds only a few representative actions. Tree-Frontier allows the agent to be likely to select near-optimal actions by being greedy over selecting the best representative action. Experimentally, we show that TRES significantly outperforms state-of-the-art methods in terms of harvest rate (ratio of relevant pages crawled), while Tree-Frontier reduces by orders of magnitude the number of actions needed to be evaluated at each timestep