Science on the Periphery. The spanish Reception of Nuclear Energy: an Attempt at Modernity?

During the Cold War, Franco’s dictatorship attempted to use technological transfer and nuclear technology to strengthen the geopolitical influence of his Government in Spain. This paper studies this process, with particular reference to the role played by German scientists as advisers to the Spanish nuclear project.     

The Market for Picasso Prints: A Hybrid Model Approach

Two basic approaches have been used by the literature focusing on the return to holding artistic works: the hedonic price model and the repeat-sales model. This paper provides a procedure for jointly estimating the two models in a way that take advantages of the unique information contained in each. A semiannual price index for Picasso prints is estimated by using a model derived from the basic framework of the hybrid models. The empirical results suggest that the hybrid model provides the most precisely estimated price index by reducing the level of price volatility.JEL Classification: C5, Z1p     

Mobile Agents for Distributed and Heterogeneous Information Retrieval

The heterogeneous, distributed and voluminous nature of many government and corporate data sources impose severe constraints on meeting the diverse requirements of users who analyze the data. Additionally, communication bandwidth limitations, time constraints, and multiple data formats impose further restrictions on users of these distributed data sources. In this paper, we present an Agent-based Complex QUerying and Information Retrieval Engine (ACQUIRE) for large, heterogeneous, and distributed data sources. ACQUIRE acts as a softbot or interface agent by presenting users with a view of a single, unified, homogenous data source, against which users can pose high-level declarative queries. ACQUIRE translates each such user query into a set of sub-queries by employing a combination of planning and traditional database query optimization techniques. ACQUIRE then spawns a set of mobile agents corresponding to these sub-queries, which in turn retrieve the data from various distributed data sources by dynamically optimizing the retrieval strategy as it is carried out. These mobile agents carry with them data-processing code that can be executed at the remote site, thus reducing the size of data returned by the agent. When all mobile agents have returned, ACQUIRE filters and merges the retrieved data and presents the results to the user. While the system is still very much a work in progress, current validation experiments on simulated NASA Distributed Active Archive Centers (DAACs) have demonstrated that complex queries can be effectively decomposed and retrieved by this approach.     

Introduction to the Special Issue on INEX

This special issue contains articles describing XML retrieval approaches developed and evaluated during the second year of INEX, the evaluation initiative for XML retrieval.     

A General Evaluation Framework for Topical Crawlers

Topical crawlers are becoming important tools to support applications such as specialized Web portals, online searching, and competitive intelligence. As the Web mining field matures, the disparate crawling strategies proposed in the literature will have to be evaluated and compared on common tasks through well-defined performance measures. This paper presents a general framework to evaluate topical crawlers. We identify a class of tasks that model crawling applications of different nature and difficulty. We then introduce a set of performance measures for fair comparative evaluations of crawlers along several dimensions including generalized notions of precision, recall, and efficiency that are appropriate and practical for the Web. The framework relies on independent relevance judgements compiled by human editors and available from public directories. Two sources of evidence are proposed to assess crawled pages, capturing different relevance criteria. Finally we introduce a set of topic characterizations to analyze the variability in crawling effectiveness across topics. The proposed evaluation framework synthesizes a number of methodologies in the topical crawlers literature and many lessons learned from several studies conducted by our group. The general framework is described in detail and then illustrated in practice by a case study that evaluates four public crawling algorithms. We found that the proposed framework is effective at evaluating, comparing, differentiating and interpreting the performance of the four crawlers. For example, we found the IS crawler to be most sensitive to the popularity of topics.Partially supported by National Science Foundation CAREER grant No. IIS-0133124/0348940.     

Rank-Stability and Rank-Similarity of Link-Based Web Ranking Algorithms in Authority-Connected Graphs

Web search algorithms that rank Web pages by examining the link structure of the Web are attractive from both theoretical and practical aspects. Todays prevailing link-based ranking algorithms rank Web pages by using the dominant eigenvector of certain matrices—like the co-citation matrix or variations thereof. Recent analyses of ranking algorithms have focused attention on the case where the corresponding matrices are irreducible, thus avoiding singularities of reducible matrices. Consequently, rank analysis has been concentrated on authority connected graphs, which are graphs whose co-citation matrix is irreducible (after deleting zero rows and columns). Such graphs conceptually correspond to thematically related collections, in which most pages pertain to a single, dominant topic of interest.A link-based search algorithm A is rank-stable if minor changes in the link structure of the input graph, which is usually a subgraph of the Web, do not affect the ranking it produces; algorithms A,B are rank-similar if they produce similar rankings. These concepts were introduced and studied recently for various existing search algorithms.This paper studies the rank-stability and rank-similarity of three link-based ranking algorithms—PageRank, HITS and SALSA—in authority connected graphs. For this class of graphs, we show that neither HITS nor PageRank is rank stable. We then show that HITS and PageRank are not rank similar on this class, nor is any of them rank similar to SALSA.This research was supported by the Fund for the Promotion of Research at the Technion, and by the Barnard Elkin Chair in Computer Science.     

Hybrid XML Retrieval: Combining Information Retrieval and a Native XML Database

This paper investigates the impact of three approaches to XML retrieval: using Zettair, a full-text information retrieval system; using eXist, a native XML database; and using a hybrid system that takes full article answers from Zettair and uses eXist to extract elements from those articles. For the content-only topics, we undertake a preliminary analysis of the INEX 2003 relevance assessments in order to identify the types of highly relevant document components. Further analysis identifies two complementary sub-cases of relevance assessments (General and Specific) and two categories of topics (Broad and Narrow). We develop a novel retrieval module that for a content-only topic utilises the information from the resulting answer list of a native XML database and dynamically determines the preferable units of retrieval, which we call Coherent Retrieval Elements. The results of our experiments show that—when each of the three systems is evaluated against different retrieval scenarios (such as different cases of relevance assessments, different topic categories and different choices of evaluation metrics)—the XML retrieval systems exhibit varying behaviour and the best performance can be reached for different values of the retrieval parameters. In the case of INEX 2003 relevance assessments for the content-only topics, our newly developed hybrid XML retrieval system is substantially more effective than either Zettair or eXist, and yields a robust and a very effective XML retrieval.