14045822
Optimizing search by showing results in context
We developed and evaluated seven interfaces for integrating semantic category information with Web search results. List interfaces were based on the familiar ranked-listing of search results, sometimes augmented with a category name for each result. Category interfaces also showed page titles and/or category names, but re-organized the search results so that items in the same category were grouped together visually. Our user studies show that all Category interfaces were more effective than List interfaces even when lists were augmented with category names for each result. The best category performance was obtained when both category names and individual page titles were presented. Either alone is better than a list presentation, but both together provide the most effective means for allowing users to quickly examining search results. These results provide a better understanding of the perceptual and cognitive factors underlying the advantage of category groupings and provide some practical guidance to Web search interface designers.
1194024
Hierarchical classification of Web content
This paper explores the use of hierarchical structure for classifying a large, heterogeneous collection of web content. The hierarchical structure is initially used to train different second-level classifiers. In the hierarchical case, a model is learned to distinguish a second-level category from other categories within the same top level. In the flat non-hierarchical case, a model distinguishes a second-level category from all other second-level categories. Scoring rules can further take advantage of the hierarchy by considering only second-level categories that exceed a threshold at the top level.
We use support vector machine (SVM) classifiers, which have been shown to be efficient and effective for classification, but not previously explored in the context of hierarchical classification. We found small advantages in accuracy for hierarchical models over flat models. For the hierarchical approach, we found the same accuracy using a sequential Boolean decision rule and a multiplicative decision rule. Since the sequential approach is much more efficient, requiring only 14%-16% of the comparisons used in the other approaches, we find it to be a good choice for classifying text into large hierarchical structures.
9276534
Setuid Demystified
1567676
Bringing order to the Web: automatically categorizing search results
We developed a user interface that organizes Web search results into hierarchical categories. Text classification algorithms were used to automatically classify arbitrary search results into an existing category structure on-the-fly. A user study compared our new category interface with the typical ranked list interface of search results. The study showed that the category interface is superior both in objective and subjective measures. Subjects liked the category interface much better than the list interface, and they were 50% faster at finding information that was organized into categories. Organizing search results allows users to focus on items in categories of interest rather than having to browse through all the results sequentially.
1402963
MOPS: an infrastructure for examining security properties of software
We describe a formal approach for finding bugs in security-relevant software and verifying their absence. The idea is as follows: we identify rules of safe programming practice, encode them as safety properties, and verify whether these properties are obeyed. Because manual verification is too expensive, we have built a program analysis tool to automate this process. Our program analysis models the program to be verified as a pushdown automaton, represents the security property as a finite state automaton, and uses model checking techniques to identify whether any state violating the desired security goal is reachable in the program. The major advantages of this approach are that it is sound in verifying the absence of certain classes of vulnerabilities, that it is fully interprocedural, and that it is efficient and scalable. Experience suggests that this approach will be useful in finding a wide range of security vulnerabilities in large programs efficiently.
7740275
FIREMAN: a toolkit for firewall modeling and analysis
Security concerns are becoming increasingly critical in networked systems. Firewalls provide important defense for network security. However, misconfigurations in firewalls are very common and significantly weaken the desired security. This paper introduces FIREMAN, a static analysis toolkit for firewall modeling and analysis. By treating firewall configurations as specialized programs, FIREMAN applies static analysis techniques to check misconfigurations, such as policy violations, inconsistencies, and inefficiencies, in individual firewalls as well as among distributed firewalls. FIREMAN performs symbolic model checking of the firewall configurations for all possible IP packets and along all possible data paths. It is both sound and complete because of the finite state nature of firewall configurations. FIREMAN is implemented by modeling firewall rules using binary decision diagrams (BDDs), which have been used successfully in hardware verification and model checking. We have experimented with FIREMAN and used it to uncover several real misconfigurations in enterprise networks, some of which have been subsequently confirmed and corrected by the administrators of these networks
6781537
Formal Models of Heavy-Tailed Behavior in Combinatorial Search
Recently, it has been found that the cost distributions of randomized backtrack search in combinatorial domains are often heavytailed. Such heavy-tailed distributions explain the high variability observed when using backtrack-style procedures. A good understanding of this phenomenon can lead to better search techniques. For example, restart strategies provide a good mechanism for eliminating the heavy-tailed behavior and boosting the overall search performance. Several state-of-the-art SAT solvers now incorporate such restart mechanisms. The study of heavy-tailed phenomena in combinatorial search has so far been been largely based on empirical data. We introduce several abstract tree search models, and show formally how heavy-tailed cost distribution can arise in backtrack search. We also discuss how these insights may facilitate the development of better combinatorial search methods.
6389142
Optimal confidence interval for the largest normal mean with unknown variance
A single-sample procedure for obtaining an optimal confidence interval for the largest or smallest mean of several independent normal populations is proposed. It is assumed that the common variance is unknown. It has been found that the optimal confidence interval is uniformly better than any other existing one-sample confidence interval in the sense of a reduced interval width. This optimal confidence interval is obtained by maximizing the coverage probability with the expected confidence width being fixed at a least favorable configuration of means. Tables of the critical values are given for the optimal confidence interval.
6987127
3D model-assisted face recognition in video
Face recognition in video has gained wide attention as a covert method for surveillance to enhance security in a variety of application domains (e.g., airports). A video contains temporal information as well as multiple instances of a face, so it is expected to lead to better face recognition performance compared to still face images. However, faces appearing in a video have substantial variations in pose and lighting. These pose and lighting variations can be effectively modeled using 3D face models. Combining the advantages of 2D video and 3D face models, we propose a face recognition system that identifies faces in a video. The system utilizes the rich information in a video and overcomes the pose and lighting variations using 3D face model. The description of the proposed method and preliminary results are provided.
20735579
Kinetically stable task assignment for networks of microservers
• Job titles for all employees • Most recent payroll data (wages, hours, job codes, and dates of hire) • Union contracts • Employee handbooks or benefit descriptions • Summary plan descriptions for health and retirement plans • Benefit costs summaries or insurance bills For a detailed listing of information that BLS economists typically request, please visit the National Compensation Survey Web site at http://www.bls.gov/ncs/collection.htm. What is the National Compensation Survey (NCS)?
15293705
Design and evaluation of a multi-agent collaborative Web mining system
Most existing Web search tools work only with individual users and do not help a user benefit from previous search experiences of others. In this paper, we present the Collaborative Spider, a multi-agent system designed to provide post-retrieval analysis and enable across-user collaboration in Web search and mining. This system allows the user to annotate search sessions and share them with other users. We also report a user study designed to evaluate the effectiveness of this system. Our experimental findings show that subjects' search performance was degraded, compared to individual search scenarios in which users had no access to previous searches, when they had access to a limited number (e.g., 1 or 2) of earlier search sessions done by other users. However, search performance improved significantly when subjects had access to more search sessions. This indicates that gain from collaboration through collaborative Web searching and analysis does not outweigh the overhead of browsing and comprehending other users' past searches until a certain number of shared sessions have been reached. In this paper, we also catalog and analyze several different types of user collaboration behavior observed in the context of Web mining.