Improving search results with data mining in a thematic search engine

The problem of obtaining relevant results in web searching has been tackled with several approaches. Although very effective techniques are currently used by the most popular search engines when no a priori knowledge on the user's desires beside the search keywords is available, in different settings it is conceivable to design search methods that operate on a thematic database of web pages that refer to a common body of knowledge or to specific sets of users. We have considered such premises to design and develop a search method that deploys data mining and optimization techniques to provide a more significant and restricted set of pages as the final result of a user search. We adopt a vectorization method based on search context and user profile to apply clustering techniques that are then refined by a specially designed genetic algorithm. In this paper we describe the method, its implementation, the algorithms applied, and discuss some experiments that has been run on test sets of web pages.     

Defining tabu list size and aspiration criterion within tabu search methods

An investigation to explicitly define two key elements in tabu search methods is attempted. In this study a functional representation of the tabu list size is presented and a softer aspiration criterion is put forward. Experiments are conducted on a set of p-median problems.Scope and purposeTabu search is a metaheuristic that proved successful in finding good solutions to difficult combinatorial problems that were hard to find otherwise. In this study, we attempt to help the user in the choice of some of the parameters used in this type of heuristics. We based our analysis on the tabu list size and on an implementation on how to define the aspiration criterion. This added information can be valuable to those users who apply these methods in a near systematic manner without relying heavily on experimentations. As an example we used a simple location problem to test the usefulness of these ideas.     

Visualization of parameter space for image analysis

Image analysis algorithms are often highly parameterized and much human input is needed to optimize parameter settings. This incurs a time cost of up to several days. We analyze and characterize the conventional parameter optimization process for image analysis and formulate user requirements. With this as input, we propose a change in paradigm by optimizing parameters based on parameter sampling and interactive visual exploration. To save time and reduce memory load, users are only involved in the first step--initialization of sampling--and the last step--visual analysis of output. This helps users to more thoroughly explore the parameter space and produce higher quality results. We describe a custom sampling plug-in we developed for CellProfiler--a popular biomedical image analysis framework. Our main focus is the development of an interactive visualization technique that enables users to analyze the relationships between sampled input parameters and corresponding output. We implemented this in a prototype called Paramorama. It provides users with a visual overview of parameters and their sampled values. User-defined areas of interest are presented in a structured way that includes image-based output and a novel layout algorithm. To find optimal parameter settings, users can tag high- and low-quality results to refine their search. We include two case studies to illustrate the utility of this approach.     

Supporting distributed product configuration by integrating heterogeneous variability modeling approaches

ContextIn industrial settings products are developed by more than one organization. Software vendors and suppliers commonly typically maintain their own product lines, which contribute to a larger (multi) product line or software ecosystem. It is unrealistic to assume that the participating organizations will agree on using a specific variability modeling technique—they will rather use different approaches and tools to manage the variability of their systems.ObjectiveWe aim to support product configuration in software ecosystems based on several variability models with different semantics that have been created using different notations.MethodWe present an integrative approach that provides a unified perspective to users configuring products in multi product line environments, regardless of the different modeling methods and tools used internally. We also present a technical infrastructure and a prototype implementation based on web services.ResultsWe show the feasibility of the approach and its implementation by using it with the three most widespread types of variability modeling approaches in the product line community, i.e., feature-based, OVM-style, and decision-oriented modeling. To demonstrate the feasibility and flexibility of our approach, we present an example derived from industrial experience in enterprise resource planning. We further applied the approach to support the configuration of privacy settings in the Android ecosystem based on multiple variability models. We also evaluated the performance of different model enactment strategies used in our approach.ConclusionsTools and techniques allowing stakeholders to handle variability in a uniform manner can considerably foster the initiation and growth of software ecosystems from the perspective of software reuse and configuration.     

Translation of Z specifications to executable code: Application to the database domain

ContextIt is well-known that the use of formal methods in the software development process results in high-quality software products. Having specified the software requirements in a formal notation, the question is how they can be transformed into an implementation. There is typically a mismatch between the specification and the implementation, known as the specification-implementation gap.ObjectiveThis paper introduces a set of translation functions to fill the specification-implementation gap in the domain of database applications. We only present the formal definition, not the implementation, of the translation functions.MethodWe chose Z, SQL and Delphi languages to illustrate our methodology. Because the mathematical foundation of Z has many properties in common with SQL, the translation functions from Z to SQL are derived easily. For the translation of Z to Delphi, we extend Delphi libraries to support Z mathematical structures such as sets and tuples. Then, based on these libraries, we derive the translation functions from Z to Delphi. Therefore, we establish a formal relationship between Z specifications and Delphi/SQL code. To prove the soundness of the translation from a Z abstract schema to the Delphi/SQL code, we define a Z design-level schema. We investigate the consistency of the Z abstract schema with the Z design-level schema by using Z refinement rules. Then, by the use of the laws of Morgan refinement calculus, we prove that the Delphi/SQL code refines the Z design-level schema.ResultsThe proposed approach can be used to build the correct prototype of a database application from its specification. This prototype can be evolved, or may be used to validate the software requirements specification against user requirements.ConclusionTherefore, the work presented in this paper reduces the overall cost of the development of database applications because early validation reveals requirement errors sooner in the software development cycle.     

Optimization modeling and analysis of trustworthiness determination strategies for service discovery of MSNP

In trustworthy service discovery for Mobile Social Networking in Proximity (MSNP), conventional trust computation faces a big challenging issue—relatively high latency. To cope with it, trustworthiness determination strategies were proposed in our previous study, aiming at avoiding trust computation under certain conditions, so as to reduce the latency. These strategies are conceived based on the assumption that data of a user’s past experience and current profile could be used, and they are incorporated with a set of thresholds from the analysis result of these data. The settings of these thresholds directly affect service quality and user satisfaction on the MSNP service, which in turn becomes an optimization problem. In this paper, we focus on formulating this optimization problem and demonstrating the effectiveness of our proposed solution by designing a simulation experiment. In detail, we establish mathematical models and adjust parameters. We conduct simulations on MATLAB and analyze the results obtained under several different settings. We further compare our work with related works. The results show that our proposed solution is practically feasible and effective in reducing latency under certain conditions.

     

The Effects of Visualization and Synchronization on Clustered-Based Mobile Web Search

ABSTRACT

Despite the increasing use of mobile web in our everyday lives, mobile web search remains a challenging task mainly due to the intensive scrolling inherent in linear presentation of search engine results (SERs) on the small screen of a mobile device. Drawing on the cognitive load theory and information foraging theory, this study aims to improve user performance in mobile web search by proposing two new artifacts—radial visualization of SERs clusters and synchronization of clusters and individual SERs presentations. These artifacts are hypothesized to improve search efficiency and/or navigation efficiency without affecting search effectiveness. This study also examines a possible moderating effect of search task type (open-ended vs. close-ended tasks). We implemented four mobile web search systems that reflect four combinations of different visualization and synchronization settings and empirically evaluated them using a controlled experiment. The results show that the radial visualization improves search efficiency and navigation efficiency, particularly for the open-ended tasks. In addition, synchronous presentation improves navigation efficiency in terms of path similarity.     

Planning and Implementing a Federated Searching System: An Examination of the Crucial Roles of Technical,Functional, and Usability Testing

SUMMARY

Federated searching software offers much promise to users as a convenient way of accessing the wealth of electronic information resources libraries provide. But metasearching is not the same as Google searching; care must be taken in organizing and presenting search options and results so that they are comprehensible to users. From software installation to usability testing and creating documentation, most of the work of implementation is behind-the-scenes and hidden from most library staff and users; however, the decisions made during implementation greatly affect staff and user experiences with the product as well as its overall utility and usability. Systematic testing of the product is necessary to make informed and defensible decisions. This article details three layers of testing (technical, functional, and usability) recommended during implementation of a federated search product, based on best practices in the literature, metasearch standards, and the authors' own experiences with implementing a locally developed broadcast search system and the federated search system WebFeat.     

Gestures and multimodal input

For users with motion impairments, the standard keyboard and mouse arrangement for computer access often presents problems. Other approaches have to be adopted to overcome this. In this paper, we will describe the development of a prototype multimodal input system based on two gestural input channels. Results from extensive user trials of this system are presented. These trials showed that the physical and cognitive loads on the user can quickly become excessive and detrimental to the interaction. Designers of multimodal input systems need to be aware of this and perform regular user trials to minimize the problem.     

SearchPad: explicit capture of search context to support Web search

Experienced users who query search engines have a complex behavior. They explore many topics in parallel, experiment with query variations, consult multiple search engines, and gather information over many sessions. In the process they need to keep track of search context — namely useful queries and promising result links, which can be hard. We present an extension to search engines called SearchPad that makes it possible to keep track of ‘search context' explicitly. We describe an efficient implementation of this idea deployed on four search engines: AltaVista, Excite, Google and Hotbot. Our design of SearchPad has several desirable properties: (i) portability across all major platforms and browsers; (ii) instant start requiring no code download or special actions on the part of the user; (iii) no server side storage; and (iv) no added client–server communication overhead. An added benefit is that it allows search services to collect valuable relevance information about the results shown to the user. In the context of each query SearchPad can log the actions taken by the user, and in particular record the links that were considered relevant by the user in the context of the query. The service was tested in a multi-platform environment with over 150 users for 4 months and found to be usable and helpful. We discovered that the ability to maintain search context explicitly seems to affect the way people search. Repeat SearchPad users looked at more search results than is typical on the Web, suggesting that availability of search context may partially compensate for non-relevant pages in the ranking.     

Tag-based user modeling for social multi-device adaptive guides

This paper aims to demonstrate that the principles of adaptation and user modeling, especially social annotation, can be integrated fruitfully with those of the web 2.0 paradigm and thereby enhance in the domain of cultural heritage. We propose a framework for improving recommender systems through exploiting the users tagging activity. We maintain that web 2.0’s participative features can be exploited by adaptive web-based systems in order to enrich and extend the user model, improve social navigation and enrich information from a bottom-up perspective. Thus our approach stresses social annotation as a new and powerful kind of feedback and as a way to infer knowledge about users. The prototype implementation of our framework in the domain of cultural heritage is named iCITY. It is serving to demonstrate the validity of our approach and to highlight the benefits of this approach specifically for cultural heritage. iCITY is an adaptive, social, multi-device recommender guide that provides information about the cultural resources and events promoting the cultural heritage in the city of Torino. Our paper first describes this system and then discusses the results of a set of evaluations that were carried out at different stages of the systems development and aimed at validating the framework and implementation of this specific prototype. In particular, we carried out a heuristic evaluation and two sets of usability tests, aimed at checking the usability of the user interface, specifically of the adaptive behavior of the system. Moreover, we conducted evaluations aimed at investigating the role of tags in the definition of the user model and the impact of tags on the accuracy of recommendations. Our results are encouraging.

Merging Results for Distributed Content Based Image Retrieval

Searching information through the Internet often requires users to separately contact several digital libraries, use each library interface to author the query, analyze retrieval results and merge them with results returned by other libraries. Such a solution could be simplified by using a centralized server that acts as a gateway between the user and several distributed repositories: The centralized server receives the user query, forwards the user query to federated repositories—possibly translating the query in the specific format required by each repository—and fuses retrieved documents for presentation to the user. To accomplish these tasks efficiently, the centralized server should perform some major operations such as: resource selection, query transformation and data fusion. In this paper we report on some aspects of MIND, a system for managing distributed, heterogeneous multimedia libraries (MIND, 2001, http://www.mind-project.org). In particular, this paper focusses on the issue of fusing results returned by different image repositories. The proposed approach is based on normalization of matching scores assigned to retrieved images by individual libraries. Experimental results on a prototype system show the potential of the proposed approach with respect to traditional solutions.     

User perceptions and expectations of an information retrieval system

Abstract

Performance measures are frequently used to evaluate user friendliness of a system. An equally important, but often overlooked factor is the users' attitudes towards a system. A prototype interface for information retrieval was developed for presenting engineering manuals online. It was tested on a representative sample of the intended end user community. We found that subjects' expectations were based on their experience with printed materials and other computer systems. Familiar search mechanisms (e.g., table of contents, index) were important for getting them started, even though they switched to other mechanisms as they gained more experience with the system. The fact that the index was more detailed than the one in the printed manual was seen by the subjects as critical for speedy and efficient information retrieval. Keyword search of the database was generally the preferred retrieval mechanism. However, some users preferred the index. The ‘Table of Contents’ which was a tree structured menu based system was found to be of limited use in the electronic medium, in contrast to the printed manual.     

Automatic integration of Web search interfaces with WISE-Integrator

An increasing number of databases are becoming Web accessible through form-based search interfaces, and many of these sources are database-driven e-commerce sites. It is a daunting task for users to access numerous Web sites individually to get the desired information. Hence, providing a unified access to multiple e-commerce search engines selling similar products is of great importance in allowing users to search and compare products from multiple sites with ease. One key task for providing such a capability is to integrate the Web search interfaces of these e-commerce search engines so that user queries can be submitted against the integrated interface. Currently, integrating such search interfaces is carried out either manually or semiautomatically, which is inefficient and difficult to maintain. In this paper, we present WISE-Integrator - a tool that performs automatic integration of Web Interfaces of Search Engines. WISE-Integrator explores a rich set of special metainformation that exists in Web search interfaces and uses the information to identify matching attributes from different search interfaces for integration. It also resolves domain differences of matching attributes. In this paper, we also discuss how to automatically extract information from search interfaces that is needed by WISE-Integrator to perform automatic interface integration. Our experimental results, based on 143 real-world search interfaces in four different domains, indicate that WISE-Integrator can achieve high attribute matching accuracy and can produce high-quality integrated search interfaces without human interactions.Received: 2 January 2004, Accepted: 25 March 2004, Published online: 12 August 2004Edited by: M. Carey     

A modular package manager architecture

ContextThe success of modern software distributions in the Free and Open Source world can be explained, among other factors, by the availability of a large collection of software packages and the possibility to easily install and remove those components using state-of-the-art package managers. However, package managers are often built using a monolithic architecture and hard-wired and ad-hoc dependency solvers implementing some customized heuristics.ObjectiveWe aim at laying the foundation for improving on existing package managers. Package managers should be complete, that is find a solution whenever there exists one, and allow the user to specify complex criteria that define how to pick the best solution according to the user’s preferences.MethodIn this paper we propose a modular architecture relying on precise interface formalisms that allows the system administrator to choose from a variety of dependency solvers and backends.ResultsWe have built a working prototype–called MPM–following the design advocated in this paper, and we show how it largely outperforms a variety of current package managers.ConclusionWe argue that a modular architecture, allowing for delegating the task of constraint solving to external solvers, is the path that leads to the next generation of package managers that will deliver better results, offer more expressive preference languages, and be easily adaptable to new platforms.     

Nearest prototype classifier designs: An experimental study

We compare eleven methods for finding prototypes upon which to base the nearest prototype classifier. Four methods for prototype selection are discussed: Wilson+Hart (a condensation+error‐editing method), and three types of combinatorial search—random search, genetic algorithm, and tabu search. Seven methods for prototype extraction are discussed: unsupervised vector quantization, supervised learning vector quantization (with and without training counters), decision surface mapping, a fuzzy version of vector quantization, c‐means clustering, and bootstrap editing. These eleven methods can be usefully divided two other ways: by whether they employ pre‐ or postsupervision; and by whether the number of prototypes found is user‐defined or “automatic.” Generalization error rates of the 11 methods are estimated on two synthetic and two real data sets. Offering the usual disclaimer that these are just a limited set of experiments, we feel confident in asserting that presupervised, extraction methods offer a better chance for success to the casual user than postsupervised, selection schemes. Finally, our calculations do not suggest that methods which find the “best” number of prototypes “automatically” are superior to methods for which the user simply specifies the number of prototypes. © 2001 John Wiley & Sons, Inc.     

View management in multimedia databases

Abstract. Though there has been extensive work on multimedia databases in the last few years, there is no prevailing notion of a multimedia view, nor there are techniques to create, manage, and maintain such views. Visualizing the results of a dynamic multimedia query or materializing a dynamic multimedia view corresponds to assembling and delivering an interactive multimedia presentation in accordance with the visualization specifications. In this paper, we suggest that a non-interactive multimedia presentation is a set of virtual objects with associated spatial and temporal presentation constraints. A virtual object is either an object, or the result of a query. As queries may have different answers at different points in time, scheduling the presentation of such objects is nontrivial. We then develop a probabilistic model of interactive multimedia presentations, extending the non-interactive model described earlier. We also develop a probabilistic model of interactive visualization where the probabilities reflect the user profiles, or the likelihood of certain user interactions. Based on this probabilistic model, we develop three utility-theoretic based types of prefetching algorithms that anticipate how users will interact with the presentation. These prefetching algorithms allow efficient visualization of the query results in accordance with the underlying specification. We have built a prototype system that incorporates these algorithms. We report on the results of experiments conducted on top of this implementation. Received June 10, 1998 / Accepted November 10, 1999     

Automated design of hierarchical intranets

This paper describes the use of i-CAD, a prototype tool for automatically synthesizing application specific intranets. i-CAD is a novel intranet computer-aided design software tool, and its ultimate goal is to concurrently design hierarchical network topologies and data management (content distribution) systems for data-intensive multimedia intranets. The prototype software tool introduced here synthesizes a three-level intranet architecture that entails minimal installation cost and yet enables all an intranet's clients to perform their tasks with acceptable performance. The tool chooses network technologies (hardware resources and protocols) based on requirements specified by the user and determines the topology. An evolutionary approach is used to search the design space for a minimal cost three-level network. The experimental results for several network design problems described here indicate the effectiveness of the prototype network tool in finding good designs from a large design space in a reasonable amount of time.     

A content search system considering the activity and context of a mobile user

People routinely carry mobile devices in their daily lives and obtain a variety of information from the Internet in many different situations. In searching for information (content) with a mobile device, a user’s activity (e.g., moving or stationary) and context (e.g., commuting in the morning or going downtown in the evening) often change, and such changes can affect the user’s degree of concentration on his or her mobile device’s display and information needs. Therefore, a search system should provide the user with an amount of information suitable for the current activity and a type of information suitable for the current context. In this study, we present the design and implementation of a content search system that considers a mobile user’s activity and context, with the goal of reducing the user’s operation load for content search. The proposed system switches between two kinds of content search systems according to the user’s activity: the location-based content search system is activated when the user is stationary (e.g., standing and sitting), while a menu-based content search system is activated when the user is moving (e.g., walking). Both systems present information according to user context. The location-based system presents detailed information via menus and a map according to location-based categories. The menu-based system presents only a few options to enable users to get content easily. Through user experiments, we confirmed that participants could get desired information more easily with this system than with a commercial search system.     

Scalable entity-based summarization of web search results using MapReduce

Although Web Search Engines index and provide access to huge amounts of documents, user queries typically return only a linear list of hits. While this is often satisfactory for focalized search, it does not provide an exploration or deeper analysis of the results. One way to achieve advanced exploration facilities exploiting the availability of structured (and semantic) data in Web search, is to enrich it with entity mining over the full contents of the search results. Such services provide the users with an initial overview of the information space, allowing them to gradually restrict it until locating the desired hits, even if they are low ranked. This is especially important in areas of professional search such as medical search, patent search, etc. In this paper we consider a general scenario of providing such services as meta-services (that is, layered over systems that support keywords search) without a-priori indexing of the underlying document collection(s). To make such services feasible for large amounts of data we use the MapReduce distributed computation model on a Cloud infrastructure (Amazon EC2). Specifically, we show how the required computational tasks can be factorized and expressed as MapReduce functions. A key contribution of our work is a thorough evaluation of platform configuration and tuning, an aspect that is often disregarded and inadequately addressed in prior work, but crucial for the efficient utilization of resources. Finally we report experimental results about the achieved speedup in various settings.