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Incorporating minimum Frobenius norm models in direct search

Custódio, Ana Luísa; Rocha, Humberto; Vicente, Luís Nunes
Fonte: Centro de Matemática da Universidade de Coimbra Publicador: Centro de Matemática da Universidade de Coimbra
Tipo: Pré-impressão
ENG
Relevância na Pesquisa
36.28%
The goal of this paper is to show that the use of minimum Frobenius norm quadratic models can improve the performance of direct-search methods. The approach taken here is to maintain the structure of directional direct-search methods, organized around a search and a poll step, and to use the set of previously evaluated points generated during a direct-search run to build the models. The minimization of the models within a trust region provides an enhanced search step. Our numerical results show that such a procedure can lead to a significant improvement of direct search for smooth, piecewise smooth, and stochastic and nonstochastic noisy problems.; FCT POCI/MAT/59442/2004, PTDC/MAT/64838/2006.

Combining meta-learning and search techniques to select parameters for support vector machines

Gomes, Taciana A. F.; Prudencio, Ricardo B. C.; Soares, Carlos; Rossi, Andre Luís Debiaso; Carvalho, André Carlos Ponce de Leon Ferreira de
Fonte: ELSEVIER SCIENCE BV; AMSTERDAM Publicador: ELSEVIER SCIENCE BV; AMSTERDAM
Tipo: Artigo de Revista Científica
ENG
Relevância na Pesquisa
36.28%
Support Vector Machines (SVMs) have achieved very good performance on different learning problems. However, the success of SVMs depends on the adequate choice of the values of a number of parameters (e.g., the kernel and regularization parameters). In the current work, we propose the combination of meta-learning and search algorithms to deal with the problem of SVM parameter selection. In this combination, given a new problem to be solved, meta-learning is employed to recommend SVM parameter values based on parameter configurations that have been successfully adopted in previous similar problems. The parameter values returned by meta-learning are then used as initial search points by a search technique, which will further explore the parameter space. In this proposal, we envisioned that the initial solutions provided by meta-learning are located in good regions of the search space (i.e. they are closer to optimum solutions). Hence, the search algorithm would need to evaluate a lower number of candidate solutions when looking for an adequate solution. In this work, we investigate the combination of meta-learning with two search algorithms: Particle Swarm Optimization and Tabu Search. The implemented hybrid algorithms were used to select the values of two SVM parameters in the regression domain. These combinations were compared with the use of the search algorithms without meta-learning. The experimental results on a set of 40 regression problems showed that...

MOOGLE: a metamodel-based model search engine

Lucredio, Daniel; Fortes, Renata Pontin de Mattos; Whittle, Jon
Fonte: SPRINGER HEIDELBERG; HEIDELBERG Publicador: SPRINGER HEIDELBERG; HEIDELBERG
Tipo: Artigo de Revista Científica
ENG
Relevância na Pesquisa
36.27%
Models are becoming increasingly important in the software development process. As a consequence, the number of models being used is increasing, and so is the need for efficient mechanisms to search them. Various existing search engines could be used for this purpose, but they lack features to properly search models, mainly because they are strongly focused on text-based search. This paper presents Moogle, a model search engine that uses metamodeling information to create richer search indexes and to allow more complex queries to be performed. The paper also presents the results of an evaluation of Moogle, which showed that the metamodel information improves the accuracy of the search.; Microsoft Research; CAPES [0657/07-7]; CNPq [141975/2008-3]; FAPESP [2008/11476-8]; FACEPE [573964/2008-4, APQ-1037-1.03/08]

Improving biodiversity data retrieval through semantic search and ontologies

Amanqui, Flor Karina Mamani; Serique, Kleberson Junio do Amaral; Cardoso, Silvio Domingos; Santos, José L. dos; Albuquerque, Andrea; Moreira, Dilvan de Abreu
Fonte: University of Warsaw; Institute of Electrical and Electronics Engineers - IEEE; Web Intelligence Consortium - WIC; Association for Computing Machinery - ACM; Warsaw Publicador: University of Warsaw; Institute of Electrical and Electronics Engineers - IEEE; Web Intelligence Consortium - WIC; Association for Computing Machinery - ACM; Warsaw
Tipo: Conferência ou Objeto de Conferência
ENG
Relevância na Pesquisa
36.3%
Due to the increased amount of available biodiversity data, many biodiversity research institutions are now making their databases openly available on the web. Researchers in the field use this databases to extract new knowledge and also share their own discoveries. However, when these researchers need to find relevant information in the data, they still rely on the traditional search approach, based on text matching, that is not appropriate to be used in these large amounts of heterogeneous biodiversity’s data, leading to search results with low precision and recall. We present a new architecture that tackle this problem using a semantic search system for biodiversity data. Semantic search aims to improve search accuracy by using ontologies to understand user objectives and the contextual meaning of terms used in the search to generate more relevant results. Biodiversity data is mapped to terms from relevant ontologies, such as Darwin Core, DBpedia, Ontobio and Catalogue of Life, stored using semantic web formats and queried using semantic web tools (such as triple stores). A prototype semantic search tool was successfully implemented and evaluated by users from the National Research Institute for the Amazon (INPA). Our results show that the semantic search approach has a better precision (28% improvement) and recall (25% improvement) when compared to keyword based search...

Uma arquitetura para sistemas de busca semântica para recuperação de informações em repositórios de biodiversidade; An architecture for semantic search systems for retrieving information in repositories of biodiversity

Amanqui, Flor Karina Mamani
Fonte: Biblioteca Digitais de Teses e Dissertações da USP Publicador: Biblioteca Digitais de Teses e Dissertações da USP
Tipo: Dissertação de Mestrado Formato: application/pdf
Publicado em 16/05/2014 PT
Relevância na Pesquisa
36.3%
A diversidade biológica é essencial para a sustentabilidade da vida na Terra e motiva numerosos esforços para coleta de dados sobre espécies, dando origem a uma grande quantidade de informação. Esses dados são geralmente armazenados em bancos de dados relacionais. Pesquisadores usam esses bancos de dados para extrair conhecimento e compartilhar novas descobertas. No entanto, atualmente a busca tradicional (baseada em palavras-chave) já não é adequada para ser usada em grandes quantidades de dados heterogêneos, como os de biodiversidade. Ela tem baixa precisão e revocação para esse tipo de dado. Este trabalho apresenta uma nova arquitetura para abordar esse problema aplicando técnicas de buscas semânticas em dados sobre biodiversidade e usando formatos e ferramentas da Web Semântica para representar esses dados. A busca semântica tem como objetivo melhorar a acurácia dos resultados de buscas com o uso de ontologias para entender os objetivos dos usuários e o significado contextual dos termos utilizados. Este trabalho também apresenta os resultados de testes usando um conjunto de dados representativos sobre biodiversidade do Instituto Nacional de Pesquisas da Amazônia (INPA) e do Museu Paraense Emílio Goeldi (MPEG). Ontologias permitem que conhecimento seja organizado em espaços conceituais de acordo com seu significado. Para a busca semântica funcionar...

Essays on Platforms: Asymmetric Information, Search, and Policy

Wang, Albert Zhao
Fonte: Harvard University Publicador: Harvard University
Tipo: Thesis or Dissertation
EN_US
Relevância na Pesquisa
36.33%
The three essays of this thesis cover two sets of topics: search in auction platforms in the first two papers, and political campaigning in the last. In platform settings, search cost reductions are often regarded as beneficial because they improve match quality. But is this in fact true? And if it is true in an aggregate sense, what are the consequences to individual platform participants? Do individual buyers and sellers win or lose? The first paper develops a novel model of search in platforms and applies it to auction platforms to test the popular hypothesis that lower search costs are always beneficial to sellers. Under certain assumptions, we find that while lower search costs is welfare improving, its distributional consequences are less predictable. In general, lower search costs intesify buyer-side competition. On the one hand, this tends to improve seller revenues due to better matches; on the other hand, this may also thin out markets for certain sellers, since lower search costs make it easier for buyers to search out of certain markets. Generally, some sellers gain and some lose; most surprisingly, however, we find that overall seller revenue can decrease with lower search costs. Our second paper extends the model to endogenize buyer participation - so some buyers may leave the platform completely - and considers optimal platform search policy in such settings. Under stricter assumptions...

Keyword Competition and Determinants of Ad Position in Sponsored Search Advertising

Karimi, Armin
Fonte: Brock University Publicador: Brock University
Tipo: Electronic Thesis or Dissertation
ENG
Relevância na Pesquisa
36.28%
Given the significant growth of the Internet in recent years, marketers have been striving for new techniques and strategies to prosper in the online world. Statistically, search engines have been the most dominant channels of Internet marketing in recent years. However, the mechanics of advertising in such a market place has created a challenging environment for marketers to position their ads among their competitors. This study uses a unique cross-sectional dataset of the top 500 Internet retailers in North America and hierarchical multiple regression analysis to empirically investigate the effect of keyword competition on the relationship between ad position and its determinants in the sponsored search market. To this end, the study utilizes the literature in consumer search behavior, keyword auction mechanism design, and search advertising performance as the theoretical foundation. This study is the first of its kind to examine the sponsored search market characteristics in a cross-sectional setting where the level of keyword competition is explicitly captured in terms of the number of Internet retailers competing for similar keywords. Internet retailing provides an appropriate setting for this study given the high-stake battle for market share and intense competition for keywords in the sponsored search market place. The findings of this study indicate that bid values and ad relevancy metrics as well as their interaction affect the position of ads on the search engine result pages (SERPs). These results confirm some of the findings from previous studies that examined sponsored search advertising performance at a keyword level. Furthermore...

Ranked Search on Data Graphs

Varadarajan, Ramakrishna R.
Fonte: FIU Digital Commons Publicador: FIU Digital Commons
Tipo: Artigo de Revista Científica Formato: application/pdf
Relevância na Pesquisa
36.32%
Graph-structured databases are widely prevalent, and the problem of effective search and retrieval from such graphs has been receiving much attention recently. For example, the Web can be naturally viewed as a graph. Likewise, a relational database can be viewed as a graph where tuples are modeled as vertices connected via foreign-key relationships. Keyword search querying has emerged as one of the most effective paradigms for information discovery, especially over HTML documents in the World Wide Web. One of the key advantages of keyword search querying is its simplicity – users do not have to learn a complex query language, and can issue queries without any prior knowledge about the structure of the underlying data. The purpose of this dissertation was to develop techniques for user-friendly, high quality and efficient searching of graph structured databases. Several ranked search methods on data graphs have been studied in the recent years. Given a top-k keyword search query on a graph and some ranking criteria, a keyword proximity search finds the top-k answers where each answer is a substructure of the graph containing all query keywords, which illustrates the relationship between the keyword present in the graph. We applied keyword proximity search on the web and the page graph of web documents to find top-k answers that satisfy user’s information need and increase user satisfaction. Another effective ranking mechanism applied on data graphs is the authority flow based ranking mechanism. Given a top-k keyword search query on a graph...

Indigenous job search success

Gray, Matthew; Hunter, Boyd
Fonte: Universidade Nacional da Austrália Publicador: Universidade Nacional da Austrália
Tipo: Working/Technical Paper Formato: 1523811 bytes; 355 bytes; application/pdf; application/octet-stream
EN_AU
Relevância na Pesquisa
36.3%
One important and under-researched aspect of labour market policy is the extent to which policy interventions are effective in modifying job search behaviour. Furthermore, there is little extant research on whether certain job search behaviours lead to labour market success. Our analysis uses the only existing largescale longitudinal survey of Indigenous Australians to examine the effects of job search behaviour over an 18-month period from March 1996. One major finding is that the introduction of the Job Search Diary during the survey period was effective in increasing search intensity—but this increase in intensity did not result in increased employment rates. Another finding is that the job search methods used were not generally related to the probability of finding and retaining employment when a range of other personal and regional factors are taken into account. Those with a greater level of search intensity (as measured by the number of jobs applied for) at the first wave of the survey did have a significantly higher probability of finding employment than those searching less intensely. However, search intensity is unrelated to the probability of job retention. Other factors, such as educational attainment, health status, region of residence and having been arrested...

Three essays on consumer search behavior in experimental market environments.

Ke, Changxia
Fonte: Universidade de Adelaide Publicador: Universidade de Adelaide
Tipo: Tese de Doutorado
Publicado em //2010
Relevância na Pesquisa
36.32%
This thesis investigates consumer search behavior in different contexts and its implications on certain market outcomes. It consists of three self-contained essays. Part one investigates if people search optimally and how price promotions (such as the provision of price discounts) influence search intensity and risk-taking behavior. We start with a typical sequential search task in a finite time horizon (with exogenously determined price dispersion) as the baseline treatment. In the two experimental treatments, exogenous discounts are introduced to the search process. The treatments differ in the amount of information on the discounts revealed to the subjects. Subjects’ search behavior is roughly consistent with optimality for a risk-neutral agent, but significantly influenced by the introduction of discount vouchers. We find that subjects’ search intensity is significantly reduced if they are in a shop that offers discounts, even when the monetary benefit induced by the discount has been taken into account. This suggests that people seem to gain extra non-monetary utility from buying a discounted product. Alternatively, subjects might overestimate the value of a discount. Following the findings in part one, we focus on price-framing effects of discounts on consumer search behavior in part two. In order to isolate the price-framing effect from all other possible influences...

Symbolic search and abstraction heuristics for cost-optimal planning in automated planning

Torralba Arias de Reyna, Álvaro
Fonte: Universidade Carlos III de Madrid Publicador: Universidade Carlos III de Madrid
Tipo: Tese de Doutorado
ENG
Relevância na Pesquisa
36.37%
La Planificación Automática puede ser definida como el problema de encontrar una secuencia de acciones (un plan) para conseguir una meta, desde un punto inicial, asumiendo que las acciones tienen efectos deterministas. La Planificación Automática es independiente de dominio porque los planificadores toman como información inicial una descripción del problema y deben resolverlo sin ninguna información adicional. Esta tesis trata en particular de planificación automática ´optima, en la cual las acciones tienen un coste asociado. Los planificadores óptimos deben encontrar un plan y probar que no existe ningún otro plan de menor coste. La mayoría de los planificadores óptimos están basados en la búsqueda de estados explícita. Sin lugar a dudas, esta aproximación ha sido la dominante en planificación automática óptima durante los últimos años. No obstante, la búsqueda simbólica se presenta como una alternativa interesante. En esta tesis, proponemos dos mejoras ortogonales para la planificación basada en búsqueda simbólica. En primer lugar, estudiamos diferentes métodos para mejorar la computación de la “imagen”, operación que calcula el conjunto de estados sucesores a partir de un conjunto de estados. Posteriormente...

Modeling and Analysis of Exhaustive Probabilistic Search

Chung, Timothy H.; Silvestrini, Rachel T.
Fonte: Escola de Pós-Graduação Naval Publicador: Escola de Pós-Graduação Naval
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
36.31%
The article of record as published may be located at http://dx.doi.org/10.1002/nav.21574; This article explores a probabilistic formulation for exhaustive search of a bounded area by a single searcher for a single static target. The searcher maintains an aggregate belief of the target’s presence or absence in the search area, concluding with a positive or negative search decision on crossing of decision thresholds. The measure of search performance is defined as the expected time until a search decision is made as well as the probability of the search decision being correct. The searcher gathers observations using an imperfect detector, that is, one with false positive and negative errors, and integrates them in an iterative Bayesian manner. Analytic expressions for the Bayesian update recursion of the aggregate belief are given, with theoretical results describing the role of positive and negative detections, as well as sensitivity results for the effect of the detection errors on the aggregate belief evolution. Statistical studies via design of simulation experiments provide insights into the significant search parameters, including imperfect sensor characteristics, initial belief value, search decision threshold values...

Modeling and integration of situational awareness and soldier target search

Evangelista, Paul F.; Darken, Christian J.; Jungkunz, Patrick
Fonte: Escola de Pós-Graduação Naval Publicador: Escola de Pós-Graduação Naval
Relevância na Pesquisa
36.28%
The article of record as published may be found at http://doi.org/DOI: 10.1177/1548512911415726; Representation of search and target acquisition (STA) in military models and simulations arguably abstracts the most critical aspects of combat. This research focuses on the search aspect of STA for the unaided human eye. It is intuitive that an individual's environmental characteristics and interpretation of the environment in the context of all comprehended information, commonly summarized as their situational awareness (SA), influences attention and search. Current simulation models use a primitive sweeping search method that devotes an unbiased amount of time to every area in an entity's field of regard and neglects to effects of SA. The goal of this research is to provide empirical results and recommend modeling approaches that improve the respresentation of unaided search in military models and simulations. The major contributions towards this goal include novel empricial results from two incermental eye-tracking experiments, analysis and modeling of the eye-tracking data to illustrate the effect of the environment and SA on search, and a recommended model for unaided search for high-fidelity combat simulation models. The results of this work support soldier search models driven by metrics that summarize the threat based on envirnomental characteristics and contextual information.

Kompetente Informationssuche im World Wide Web. Entwicklung und Evaluation eines Webtrainings für Schüler; Competent information search in the World Wide Web. Development and evaluation of a Web training for pupils

Schorr, Tina
Fonte: Universität Tübingen Publicador: Universität Tübingen
Tipo: Dissertation; info:eu-repo/semantics/doctoralThesis
DE_DE
Relevância na Pesquisa
36.35%
In der modernen Informationsgesellschaft besteht die Notwendigkeit, ständig über neue Informationen zu den unterschiedlichsten Themen zu verfügen. Dies setzt unter anderem die eigenständige Nutzung von Informationsangeboten voraus, wobei das WWW zu den bevorzugten Informationsumgebungen zählt. Dabei stellt das Web auf Grund seiner besonderen Eigenschaften spezifische Anforderungen an seine Nutzer, die von der Orientierung im Informationsangebot über die Evaluation von Informationsquellen bis zur Selektion relevanter Informationen reichen. Die Vermittlung des für eine erfolgreiche Informationssuche im Web erforderlichen Wissens auf Nutzerseite wird gemeinhin als schulische Aufgabe angesehen, wobei aber die Effektivität der hierzu häufig eingesetzten Internetführerscheine anzuzweifeln ist. Solche Internetführerscheine sind nämlich meist durch eine starke Technikorientierung gekennzeichnet, welche zu Lasten der - aus psychologischer Sicht entscheidenden - Wissensvermittlung zum kompetenten Umgang mit Informationen geht. Daher wurde das Webtraining KIS-WEB (Kompetente InformationsSuche im World Wide WEB) für Schüler als Zielgruppe entwickelt, das den kompetenten Umgang mit Informationen in den Mittelpunkte stellt. Das Training basiert auf zwei theoretischen Analysen: In einer konzeptionellen Analyse...

Separating the wheat from the chaff: The role of evaluation instructions, user characteristics, and the search interface in evaluating information quality during Web search on medical and health-related issues; Die Spreu vom Weizen trennen: Der Einfluss von Bewertungsinstruktionen, Personeneigenschaften, und des Suchmaschinen-Interface auf die Bewertung der Informationsqualität bei der Webrecherche zu medizinischen und gesundheitlichen Themen

Kammerer, Yvonne
Fonte: Universität Tübingen Publicador: Universität Tübingen
Tipo: Dissertation; info:eu-repo/semantics/doctoralThesis
EN
Relevância na Pesquisa
36.37%
The World Wide Web has become a major resource for medical and health information. However information on the Web varies considerably, with many Web sites containing one-sided, biased, or even false information. Thus, it has become more and more important for Web searchers to critically evaluate the information quality, in order to "separate the wheat from the chaff". Therefore, the purpose of this dissertation was to investigate under which preconditions and to what extent laypersons engage in evaluations of information quality during Web search for a conflicting medical or health-related issue. The dissertation is grounded in theory and prior research related to the information foraging theory (Pirolli, 2007; Pirolli & Card, 1999) and the documents model framework (Perfetti et al., 1999, Rouet, 2006), as well as in research from the field of information science (e.g., Rieh, 2002). Based on a conceptual framework proposed by Lazonder and Rouet (2008) three different types of variables that may influence the evaluation of information quality during Web search were examined, namely contextual variables, individual variables, and resource variables. To collect data on participants' (i.e., university students') evaluation processes during Web search...

Towards Next Generation Vertical Search Engines

Zheng, Li
Fonte: FIU Digital Commons Publicador: FIU Digital Commons
Tipo: Artigo de Revista Científica Formato: application/pdf
Relevância na Pesquisa
36.31%
As the Web evolves unexpectedly fast, information grows explosively. Useful resources become more and more difficult to find because of their dynamic and unstructured characteristics. A vertical search engine is designed and implemented towards a specific domain. Instead of processing the giant volume of miscellaneous information distributed in the Web, a vertical search engine targets at identifying relevant information in specific domains or topics and eventually provides users with up-to-date information, highly focused insights and actionable knowledge representation. As the mobile device gets more popular, the nature of the search is changing. So, acquiring information on a mobile device poses unique requirements on traditional search engines, which will potentially change every feature they used to have. To summarize, users are strongly expecting search engines that can satisfy their individual information needs, adapt their current situation, and present highly personalized search results. In my research, the next generation vertical search engine means to utilize and enrich existing domain information to close the loop of vertical search engine's system that mutually facilitate knowledge discovering, actionable information extraction...

Search engine advertising in web retailing : an efficiency analysis

Mokaya, Brian O.
Fonte: Brock University Publicador: Brock University
Tipo: Electronic Thesis or Dissertation
ENG
Relevância na Pesquisa
36.36%
This study examines the efficiency of search engine advertising strategies employed by firms. The research setting is the online retailing industry, which is characterized by extensive use of Web technologies and high competition for market share and profitability. For Internet retailers, search engines are increasingly serving as an information gateway for many decision-making tasks. In particular, Search engine advertising (SEA) has opened a new marketing channel for retailers to attract new customers and improve their performance. In addition to natural (organic) search marketing strategies, search engine advertisers compete for top advertisement slots provided by search brokers such as Google and Yahoo! through keyword auctions. The rationale being that greater visibility on a search engine during a keyword search will capture customers' interest in a business and its product or service offerings. Search engines account for most online activities today. Compared with the slow growth of traditional marketing channels, online search volumes continue to grow at a steady rate. According to the Search Engine Marketing Professional Organization...

Improving Code Search Using Learning-to-Rank and Query Reformulation Techniques

Niu, HAORAN
Fonte: Quens University Publicador: Quens University
Tipo: Tese de Doutorado
EN; EN
Relevância na Pesquisa
36.3%
During the process of software development, developers often encounter unfamiliar programming tasks. Online Q&A forums, such as StackOverflow, are one of the resources that developers can ask for answers to their programming questions. Automatic recommendation of a working code example can be helpful to solve developers’ programming questions. However, existing code search engines support mainly keyword-based queries, and do not accomodate well natural-language code search queries. Specifically, natural-language queries contain less technical keywords, i.e., class or method names, which negatively affects the success of the code search process of existing code search engines. On the other hand, a code search engine requires a ranking schema to place relevant code examples at the top of the result list. However, existing ranking schemas are hand-crafted heuristics where the configurations are hard to determine, which leads to the difficulty in using them for new languages or frameworks. In this paper, we propose the approach which uses query reformulation techniques to improve the search effectiveness of existing code search engines for naturallanguage queries. The approach automatically reformulate natural-language queries using class-names with semantic relations. We also propose an approach to automatically train a ranking schema for the code example search using the learning-to-rank technique. We evaluate the proposed approaches using a large-scale corpus of code examples. The evaluation results show that our approaches can effectively recommend semantically related class-names to reformulate natural-language queries...

Variation in Visual Search Abilities and Performance

Clark, Kait
Fonte: Universidade Duke Publicador: Universidade Duke
Tipo: Dissertação
Publicado em //2014
Relevância na Pesquisa
36.32%

Visual search, the process of detecting relevant items within an environment, is a vital skill required for navigating one's visual environment as well as for careers, such as radiology and airport security, that rely upon accurate searching. Research over the course of several decades has established that visual search requires the integration of low- and high-level cognitive processes, including sensory analysis, attentional allocation, target discrimination, and decision-making. Search abilities are malleable and vary in accordance with long-term experiences, direct practice, and contextual factors in the immediate environment; however, the mechanisms responsible for changes in search performance remain largely unclear. A series of studies examine variation in visual search abilities and performance and aim to identify the underlying mechanisms.

To assess differences associated with long-term experiences, visual search performance is compared between laypersons (typically undergraduates) and specific populations, including radiologists and avid action video game players. Behavioral markers of search processes are used to elucidate causes of enhanced search performance. To assess differences associated with direct practice...

A Search Optimization in FFTW

Gu, Liang
Fonte: University of Delaware Publicador: University of Delaware
Tipo: Tese de Doutorado
Relevância na Pesquisa
36.31%
Li, Xiaoming; Generating high performance fast Fourier transform(FFT) libraries for different computer architectures is an important task. Architecture vendors sometimes have to rely on dedicated experts to tune FFT implementation on each new platform. Fastest Fourier transform in the West(FFTW) replaces this tedious and repeated work with an adaptive FFT library. It automatically generates FFT code that are comparable to libraries provided by vendors. Part of its success is due to its highly e cient straight-line style code for small DFTs, called codelets. The other part of its success is the result of a large and carefully chosen search space of FFT algorithms. FFTW mainly traverses this space by empirical search, otherwise a simple heuristic is used. However, both methods have their downside. The empirical search method spends a lot of search time on large DFT problems and the simple heuristic often delivers implementation that is much worse than optimum. An ideal approach should nd a reasonably good implementation within the FFT search space in a small amount of time. Model-driven optimization is often believed to be inferior to empirical search. It is very hard to capture all the performance features of an adaptive library on many modern architectures. No one has implemented an adaptive performance model to automatically assist the search of FFT algorithms on multiple architectures. This thesis presents an implicit abstract machine model and a codelet performance model that can be used in the current FFTW framework. With the performance prediction given by these models...