12875596
Exploring patterns of social commonality among file directories at work
We studied files stored by members of a work organization for patterns of social commonality. Discovering identical or similar documents, applications, developer libraries, or other files may suggest shared interests or experience among users. Examining actual file data revealed a number of individual and aggregate practices around file storage. For example, pairs of users typically have many (over 13,000) files in common. A prototype called LiveWire exploits this commonality to make file backup and restore more efficient for a work organization. We removed commonly shared files and focused on specific filetypes that represent user activity to find more meaningful files in common. The Consolidarity project explores how patterns of file commonality could encourage social networking in an organizational context. Mechanisms for addressing the privacy concerns raised by this approach are discussed.
6543572
Findings from Observational Studies of Collaborative Work
Abstract The work activity of small groups of three to four people was videotaped and analysed in order to understand collaborative work and to guide the development of tools to support it. The analysis focused on the group's shared drawing activity—their listing, drawing, gesturing and talking around a shared drawing surface. This analysis identified specific features of collaborative work activity that raise design implications for collaborative technology: (1) collaborators use hand gestures to uniquely communicate significant information; (2) the process of creating and using drawings conveys much information not contained in the resulting drawings; (3) the drawing space is an important resource for the group in mediating their collaboration; (4) there is a fluent mix of activity in the drawing space; and (5) the spatial orientation among the collaborators and the drawing space has a role in structuring their activity. These observations are illustrated with examples from the video data, and the design implications they raise are discussed.
10355154
Supporting distributed groups with a Montage of lightweight interactions
The Montage prototype provides lightweight audio-video glances among distributed collaborators and integrates other applications for coordinating future contact. We studied a distributed group across three conditions: before installing Montage, with Montage, and after removing Montage. We collected quantitative measures of usage as well as video-tape and user perception data. We found that the group used Montage glances for short, lightweight interactions that were like face-to-face conversations in many respects. Yet like the phone, Montage offered convenient access to other people without leaving the office. Most glances revealed that the person was not available, so it was important to integrate other tools for coordinating future interaction. Montage did not appear to displace the use of e-mail, voice-mail, or scheduled meetings.
18533540
Beyond Instant Messaging
The recent rise in popularity of IM (instant messaging) has driven the developmentof platforms and the emergence of standards to support IM. Especially as theuse of IM has migrated from online socializing at home to business settings,there is a need to provide robust platforms with the interfaces that businesscustomers use to integrate with other work applications. Yet, in the rush todevelop a mature IM infrastructure, it is also important to recognize that IMfeatures and uses are still evolving. For example, popular press stories1 haveraised the concern that IM interactions may be too distracting in the workplace.This concern suggests that we still need to fine-tune the interface design forIM so the benefits of quick, lightweight communication can be gained withoutcreating a distracting burden for users. How can the industry meet the demandfor robust platforms and standards for IM without locking out innovation anddevelopment?
43821577
When Can I Expect an Email Response? A Study of Rhythms in Email Usage
A study of email responsiveness was conducted to understand how the timing of email responses conveys important information. Interviews and observations explored users' perceptions of how they responded to email and formed expectations of others' responses to them. We identified ways in which users maintain and cultivate a responsiveness image for projecting expectations about their email response. We also discuss other contextual cues people use to discover email responsiveness, which include using other tools such as the calendar and phone, accounting for the amount of work time overlap available, and establishing a pacing between email correspondents. These cues help users develop a sense of when to expect a response and when breakdown has occurred, requiring further action.
1186186
Piazza: a desktop environment supporting impromptu and planned interactions
Much of the support for communication across distributed communities has focused on meetings and intentional contact. However, most interactions within co-located groups occur when people happen to run into each other. Such unintended interactions should also be supported among distributed communities. We conducted a study of the communication patterns of a large, distributed organization and found that people tend to disseminate information using formal techniques, even though people usually receive information informally. We then designed a system called Piazza that is intended to support the range of communication styles evident in large communities, paying particular attention to adchessing the problems revealed in our study. Piazza allows people to be aware of others who are doing similar tasks when they are using their computers, the~by enabling unintended interactions. It also supports intentiomd contacts and planned meetings. We discuss issues for analysis in an upcoming use study.
37720806
An efficient method for mutual exclusion in truly distributed systems
Many operations in a distributed system require mutual exclusion to guarantee correctness. Quorum methods have been widely proposed for implementing mutual exclusion. Majority voting is the best known quorum method. It has the merit of simplicity, but may incur high message overhead. The tree algorithm is an efficient structured quorum method for mutual exclusion problems. The quorums generated by a tree algorithm are smaller on average than those generated by a majority voting. However, the tree algorithm enforces a highly biased treatment to the nodes at different levels. This affects its performance in a distributed system where the nodes have similar characteristics. We propose a new structured quorum method which treats the nodes more evenly than the tree algorithm yet still preserves a satisfactory availability. We believe that this method is desirable for implementing mutual exclusion in a truly distributed system.<<ETX>>
10131271
Hierarchical Classification of Documents with Error Control
Classification is a function that matches a new object with one of the predefined classes. Document classification is characterized by the large number of attributes involved in the objects (documents). The traditional method of building a single classifier to do all the classification work would incur a high overhead. Hierarchical classification is a more efficient method -- instead of a single classifier, we use a set of classifiers distributed over a class taxonomy, one for each internal node. However, once a misclassification occurs at a high level class, it may result in a class that is far apart from the correct one. An existing approach to coping with this problem requires terms also to be arranged hierarchically. In this paper, instead of overhauling the classifier itself, we propose mechanisms to detect misclassification and take appropriate actions. We then discuss an alternative that masks the misclassification based on a well known software fault tolerance technique. Our experiments show our algorithms represent a good trade-off between speed and accuracy in most applications.
4332072
A Component Retrieval Method Based on Facet-Weight Self-learning
Component-based development method has been a new software development paradigm. How to get the needed components quickly and accurately is one of the basic problems about reusing software component automatically. In this paper, an intelligent component retrieval model – FWRM. is proposed. Facet presentation is used to model query and component. Multiple types of facets are defined which extends traditional keyword-based facet presentation. Genetic algorithm based facet weight self-learning algorithm can change the facet weight dynamically in order to improve retrieval accuracy. Corresponding similarity functions are defined also. In addition, risk minimization-based component sampling method is used to solve the insufficiency of training data. All these algorithms and methods are integrated into FWRM’s three main implementation parts: Facet-Weight Optimize System, Component Retrieve System and Resource. The experimental results prove that this method is feasible and can improve component retrieval effectively.
39775533
Research of Atomic and Anonymous Electronic Commerce Protocol
Atomicity and anonymity are the two important requirements for application in electronic commerce. However absolutely anonymity may lead to confliction with law enforcement, e.g. blackmailing or money laundering. Therefore, it is important to design systems satisfying both atomicity and revocable anonymity. Based on the concept of two-phase commitment, we realize atomicity in electronic transaction with the Trusted Third Part as coordinator. Also we develops Brands' fair signature model, propose a method to enable not only anonymity but also owner-trace and money-trace.
4300632
Keyword Extraction Using Support Vector Machine
This paper is concerned with keyword extraction. By keyword extraction, we mean extracting a subset of words/phrases from a document that can describe the ‘meaning' of the document. Keywords are of benefit to many text mining applications. However, a large number of documents do not have keywords and thus it is necessary to assign keywords before enjoying the benefit from it. Several research efforts have been done on keyword extraction. These methods make use of the ‘global context information', which makes the performance of extraction restricted. A thorough and systematic investigation on the issue is thus needed. In this paper, we propose to make use of not only ‘global context information', but also ‘local context information' for extracting keywords from documents. As far as we know, utilizing both ‘global context information' and ‘local context information' in keyword extraction has not been sufficiently investigated previously. Methods for performing the tasks on the basis of Support Vector Machines have also been proposed in this paper. Features in the model have been defined. Experimental results indicate that the proposed SVM based method can significantly outperform the baseline methods for keyword extraction. The proposed method has been applied to document classification, a typical text mining processing. Experimental results show that the accuracy of document classification can be significantly improved by using the keyword extraction method.