MIRACLE at Ad-Hoc CLEF 2005: Merging and Combining Without Using a Single Approach

This paper presents the 2005 Miracle’s team approach to the Ad-Hoc Information Retrieval tasks. The goal for the experiments this year was twofold: to continue testing the effect of combination approaches on information retrieval tasks, and improving our basic processing and indexing tools, adapting them to new languages with strange encoding schemes. The starting point was a set of basic components: stemming, transforming, filtering, proper nouns extraction, paragraph extraction, and pseudo-relevance feedback. Some of these basic components were used in different combinations and order of application for document indexing and for query processing. Second-order combinations were also tested, by averaging or selective combination of the documents retrieved by different approaches for a particular query. In the multilingual track, we concentrated our work on the merging process of the results of monolingual runs to get the overall multilingual result, relying on available translations. In both cross-lingual tracks, we have used available translation resources, and in some cases we have used a combination approach

GeoCLEF 2006: the CLEF 2006 Ccross-language geographic information retrieval track overview

After being a pilot track in 2005, GeoCLEF advanced to be a regular track within CLEF 2006. The purpose of GeoCLEF is to test and evaluate cross-language geographic information retrieval (GIR): retrieval for topics with a geographic specification. For GeoCLEF 2006, twenty-five search topics were defined by the organizing groups for searching English, German, Portuguese and Spanish document collections. Topics were translated into English, German, Portuguese, Spanish and Japanese. Several topics in 2006 were significantly more geographically challenging than in 2005. Seventeen groups submitted 149 runs (up from eleven groups and 117 runs in GeoCLEF 2005). The groups used a variety of approaches, including geographic bounding boxes, named entity extraction and external knowledge bases (geographic thesauri and ontologies and gazetteers)

Managing the Knowledge Creation Process of Large-Scale Evaluation Campaigns

Περιέχει το πλήρες κείμενοThis paper discusses the evolution of large-scale evaluation campaigns and the corresponding evaluation infrastructures needed to carry them out. We present the next challenges for these initiatives and show how digital library systems can play a relevant role in supporting the research conducted in these fora by acting as virtual research environments

Overview of iCLEF 2008: Search Log Analysis for Multilingual Image Retrieval.

This paper summarises activities from the iCLEF 2008 task. In an attempt to encourage greater participation in user-orientated experiments, a new task was organised based on users participating in an interactive cross-language image search experiment. Organizers provided a default multilingual search system which accessed images from Flickr, with the whole iCLEF experiment run as an online game. Interaction by users with the system was recorded in log files which were shared with participants for further analyses, and provide a future resource for studying various effects on user-orientated cross-language search. In total six groups participated in iCLEF, providing a combined effort in generating results for a shared experiment on user-orientated cross-language retrieval

Experiments on Statistical Approaches to Compensate for Limited Linguistic Resources

Information Retrieval systems can benefit from advanced linguistic resources when carrying out tasks such as word-stemming or query translation. The main goal of our experiments has been the development of methodologies that minimize the human labor needed for creating linguistic resources for new languages. For this purpose, we have applied statistical techniques to extract information directly from the collections

An a VLSI driving circuit for memristor-based STDP

The main goal in realizing aVLSI (analog VLSI) systems able to mimic functionalities of biological neural networks is pointed to the reproduction of realistic synapses. Indeed, because of the relative high synapse/neuron ratio, especially in the case of extremely dense networks (i.e., reproduction of a real scenario), synapses represent a considerable limitation in terms of waste of silicon area and power consumption as well. Thanks to advancement made in the implementation of memristor, the interest in bio-inspired neural network design has been renewed. Memristors have tunable resistance which depends on its past state; this is analogous to the operating mode of biological synapses. In this paper, we present the circuit implementation of a simple memristor-based neural network. Here, we propose a driving circuit model that not requires specific shape input pulses to change the memristor conductance (i.e., synaptic strength), but it can be driven by arbitrary shaped input pulses. Moreover, this prototype circuit offers the chance of emulating the standard STDP behavior allowing “controlled” changes for the synaptic weights. Some preliminary experimental results are reported to validate the proposed driving circui

Information Access through Search Engines and Digital Libraries

The Information Management Systems group at the University of Padua, led by Maristella Agosti, has been a major contributor to information retrieval (IR) and digital libraries for nearly twenty years. This group has gained an excellent reputation in the IR community and has produced some of the best-known IR researchers, whose work spans a broad range of topics. The papers in this book deal with e.g. automated text categorizations, web link analysis algorithms, retrieval in multimedia digital libraries, and multilingual information retrieval. The presentation of original research results built on the past work of the group which at the same time summarizes past findings and opens up new directions and new areas of possible future research and cooperation will appeal to researchers and developers in institutions and companies working on search engines and information retrieval algorithms