Pattern Recognition

Schalkoff, Robert J.

doi:10.1002/047134608x.w5513

Cited by 9 publications

(13 citation statements)

References 23 publications

(7 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…This constraint recalls the definition of a threshold policy (19) for the workload relaxation. We take τ = τ * in our main results, and the function h is also designed using inspiration from the workload relaxation.…”

Section: Asymptotic Optimalitymentioning

confidence: 99%

“…This is a transplant option for candidates who have a living donor who is medically able, but cannot donate a kidney to their intended candidate because they are incompatible (i.e., poorly matched) [1]. In this application, or application to resource allocation (such as in scheduling in a power grid) [5,20], or pattern recognition [19], data arrives sequentially and randomly, so that matching decisions must be made in real-time, taking into account the uncertainty of future requirements for supply or demand, or the uncertainty of the sequence of classification tasks to be undertaken. The choice of matching decisions can be cast as an optimal control problem for a dynamic matching model.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Approximate optimality with bounded regret in dynamic matching models

Buýić

Meyn

2015

SIGMETRICS Perform. Eval. Rev.

View full text Add to dashboard Cite

We consider a discrete-time bipartite matching model with random arrivals of units of supply and demand that can wait in queues located at the nodes in the network. A control policy determines which are matched at each time. The focus is on the infinite-horizon average-cost optimal control problem. A relaxation of the stochastic control problem is proposed, which is found to be a special case of an inventory model, as treated in the classical theory of Clark and Scarf. The optimal policy for the relaxation admits a closed-form expression. Based on the policy for this relaxation, a new matching policy is proposed. For a parameterized family of models in which the network load approaches capacity, this policy is shown to be approximately optimal, with bounded regret, even though the average cost grows without bound.

show abstract

Section: Asymptotic Optimalitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Approximate optimality with bounded regret in dynamic matching models

Buýić

Meyn

2015

SIGMETRICS Perform. Eval. Rev.

View full text Add to dashboard Cite

show abstract

“…Entre los inconvenientes señalados en relación a este procedimiento destaca la decisión previa sobre el número de grupos que desean formarse (Amorim y Hennig, 2015;Huang, 1998). Para resolver este problema, se ha aplicado uno de los criterios más conocidos disponibles estadística-mente, denominado Sum of Squared Errors (SSE) (Celebi y otros, 2013;Schalkoff, 2001). En consecuencia, se establecen los siguientes apartados en esta sección, correspondientes a las sucesivas fases llevadas a cabo: Determinación del número de grupos, validación del agrupamiento y análisis de los grupos.…”

Section: Grupos De Usuariosunclassified

Determinación de grupos de usuarios de bibliotecas digitales mediante el análisis de ficheros log

Martínez-Comeche

2017

Rev. esp. doc. cient.

View full text Add to dashboard Cite

Resumen: En este estudio se analiza el modo en que los usuarios realizan tareas de búsqueda y recuperación de información mediante consulta en la Biblioteca Digital Hispánica, distinguiendo grupos de usuarios en función de su distinto comportamiento informacional. Para ello se emplean los ficheros log recopilados por el servidor durante un año y se cotejan distintos algoritmos de agrupamiento. Se observa que el algoritmo k-means es un procedimiento de agrupamiento adecuado al análisis de extensos ficheros log de consultas en bibliotecas digitales. En el caso de la Biblioteca Digital Hispánica se distinguen tres grupos de usuarios cuyo comportamiento informacional distintivo se describe. Palabras clave:Agrupamiento; algoritmo k-means; bibliotecas digitales; ficheros log; análisis de ficheros de transacciones; Biblioteca Digital Hispánica. Clustering of users of digital libraries through log file analysisAbstract: This study analyzes how users perform information retrieval tasks when introducing queries to the Hispanic Digital Library. Clusters of users are differentiated based on their distinct information behavior. The study used the log files collected by the server over a year and different possible clustering algorithms are compared. The k-means algorithm is found to be a suitable clustering method for the analysis of large log files from digital libraries. In the case of the Hispanic Digital Library the results show three clusters of users and the characteristic information behavior of each group is described.

show abstract

“…a set of sites. The method is related to the Fisher's linear discriminant (Schalkoff, 1992:90ff) and the information retrieval measures precision and recall. In essence, we would like to find items that distinguish sites in the target cluster from the sites outside it (possibly belonging to multiple clusters), but we also prefer the items that exhibit little variation within the target cluster.…”

Section: Finding Typical Features or ''Shibboleths''mentioning

confidence: 99%

Using Gabmap

Leinonen

Çöltekin

Nerbonne

2016

Lingua

View full text Add to dashboard Cite

Gabmap is a freely available, open-source web application that analyzes the data of language variation, e.g. varying words for the same concepts, varying pronunciations for the same words, or varying frequencies of syntactic constructions in transcribed conversations. Gabmap is an integrated part of CLARIN (see e.g. http://portal.clarin.nl). This article summarizes Gabmap's basic functionality, adding material on some new features and reporting on the range of uses to which Gabmap has been put. Gabmap is modestly successful, and its popularity underscores the fact that the study of language variation has crossed a watershed concerning the acceptability of automated language analysis. Automated analysis not only improves researchers' efficiency, it also improves the replicability of their analyses and allows them to focus on inferences to be drawn from analyses and other more abstract aspects of that study.

show abstract

Pattern Recognition

Abstract: The sections in this article are Patterns and Features Statistical Pattern Recognition (StatPR) Syntactic (Structural) Pattern Recognition Neural Pattern Recognition

Cited by 9 publications

References 23 publications

Approximate optimality with bounded regret in dynamic matching models

Approximate optimality with bounded regret in dynamic matching models

Determinación de grupos de usuarios de bibliotecas digitales mediante el análisis de ficheros log

Using Gabmap

Contact Info

Product

Resources

About