Matching Function (matching + function)

Distribution by Scientific Domains


Selected Abstracts


Did the Hartz Reforms Speed-Up the Matching Process?

GERMAN ECONOMIC REVIEW, Issue 3 2009
A Macro-Evaluation Using Empirical Matching Functions
Empirical matching function; stock-flow matching; Hartz reform Abstract. Starting in January 2003, Germany implemented the first two so-called Hartz reforms, followed by the third and fourth packages of Hartz reforms in January 2004 and January 2005, respectively. The aim of these reforms was to accelerate labor market flows and reduce unemployment duration. Without attempting to evaluate the specific components of these Hartz reforms, this paper provides a first attempt to evaluate the overall effectiveness of the first two reform waves, Hartz I/II and III, in speeding up the matching process between unemployed and vacant jobs. The analysis is conceptually rooted in the flow-based view underlying the reforms, estimating the structural features of the matching process. The results indicate that the reforms indeed had an impact in making the labor market more dynamic and accelerating the matching process. [source]


Tuning the matching function for a threshold weighting semantics in a linguistic information retrieval system

INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, Issue 9 2005
E. Herrera-Viedma
Information retrieval is an activity that attempts to produce documents that better fulfill user information needs. To achieve this activity an information retrieval system uses matching functions that specify the degree of relevance of a document with respect to a user query. Assuming linguistic-weighted queries we present a new linguistic matching function for a threshold weighting semantics that is defined using a 2-tuple fuzzy linguistic approach (Herrera F, Martínez L. IEEE Trans Fuzzy Syst 2000;8:746,752). This new 2-tuple linguistic matching function can be interpreted as a tuning of that defined in "Modelling the Retrieval Process for an Information Retrieval System Using an Ordinal Fuzzy Linguistic Approach" (Herrera-Viedma E. J Am Soc Inform Sci Technol 2001;52:460,475). We show that it simplifies the processes of computing in the retrieval activity, avoids the loss of precision in final results, and, consequently, can help to improve the users' satisfaction. © 2005 Wiley Periodicals, Inc. Int J Int Syst 20: 921,937, 2005. [source]


Applying incremental tree induction to retrieval from manuals and medical texts

JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE AND TECHNOLOGY, Issue 5 2006
Kieran J. White
The Decision Tree Forest (DTF) is an architecture for information retrieval that uses a separate decision tree for each document in a collection. Experiments were conducted in which DTFs working with the incremental tree induction (ITI) algorithm of Utgoff, Berkman, and Clouse (1997) were trained and evaluated in the medical and word processing domains using the Cystic Fibrosis and SIFT collections. Performance was compared with that of a conventional inverted index system (IIS) using a BM25-derived probabilistic matching function. Initial results using DTF were poor compared to those obtained with IIS. We then simulated scenarios in which large quantities of training data were available, by using only those parts of the document collection that were well covered by the data sets. Consequently the retrieval effectiveness of DTF improved substantially. In one particular experiment precision and recall for DTF were 0.65 and 0.67 respectively, values that compared favorably with values of 0.49 and 0.56 for IIS. [source]


Matching Efficiency and Labour Market Reform in Italy: A Macroeconometric Assessment

LABOUR, Issue 1 2007
Sergio Destefanis
We re-parameterize the matching function as a Beveridge Curve and estimate it as a production frontier, finding huge differences in matching efficiency between the South and the rest of the country. The Treu Act appears to have improved matching efficiency in the North of the country, particularly for skilled workers, but also to have strengthened competition among skilled and unskilled workers, especially in the South. [source]


Tuning the matching function for a threshold weighting semantics in a linguistic information retrieval system

INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, Issue 9 2005
E. Herrera-Viedma
Information retrieval is an activity that attempts to produce documents that better fulfill user information needs. To achieve this activity an information retrieval system uses matching functions that specify the degree of relevance of a document with respect to a user query. Assuming linguistic-weighted queries we present a new linguistic matching function for a threshold weighting semantics that is defined using a 2-tuple fuzzy linguistic approach (Herrera F, Martínez L. IEEE Trans Fuzzy Syst 2000;8:746,752). This new 2-tuple linguistic matching function can be interpreted as a tuning of that defined in "Modelling the Retrieval Process for an Information Retrieval System Using an Ordinal Fuzzy Linguistic Approach" (Herrera-Viedma E. J Am Soc Inform Sci Technol 2001;52:460,475). We show that it simplifies the processes of computing in the retrieval activity, avoids the loss of precision in final results, and, consequently, can help to improve the users' satisfaction. © 2005 Wiley Periodicals, Inc. Int J Int Syst 20: 921,937, 2005. [source]


Scale Effects in Markets with Search,

THE ECONOMIC JOURNAL, Issue 508 2006
Barbara Petrongolo
Estimates of aggregate matching functions may miss important scale effects in frictional labour markets because of the reactions of job seekers to scale. We estimate a semi-structural model of search and matching on a British sample of unemployed people, testing for scale effects on the probability of receiving an offer and on the distribution of wage offers. We find them only in wage offers but we also find that reservation wages rise to deliver higher post-unemployment wages but not faster matches. So aggregate matching functions should be unaffected by scale but wage equations should be showing them. [source]