Basics of qualitative research: Grounded theory procedures and techniques

A fundamental problem that confronts peer-to-peer applications is to efficiently locate the node that stores a particular data item. This paper presents Chord, a distributed lookup protocol that addresses this problem. Chord provides support for just one operation: given a key, it maps the key onto a node. Data location can be easily implemented on top of Chord by associating a key with each data item, and storing the key/data item pair at the node to which the key maps. Chord adapts efficiently as nodes join and leave the system, and can answer queries even if the system is continuously changing. Results from theoretical analysis, simulations, and experiments show that Chord is scalable, with communication cost and the state maintained by each node scaling logarithmically with the number of Chord nodes.

Chord: A scalable peer-to-peer lookup service for internet applications

The network structure of a hyperlinked environment can be a rich source of information about the content of the environment, provided we have effective means for understanding it. We develop a set of algorithmic tools for extracting information from the link structures of such environments, and report on experiments that demonstrate their effectiveness in a variety of context on the World Wide Web. The central issue we address within our framework is the distillation of broad search topics, through the discovery of “authorative” information sources on such topics. We propose and test an algorithmic formulation of the notion of authority, based on the relationship between a set of relevant authoritative pages and the set of “hub pages” that join them together in the link structure. Our formulation has connections to the eigenvectors of certain matrices associated with the link graph; these connections in turn motivate additional heuristrics for link-based analysis.

/pdf/authoritative-sources-in-a-hyperlinked-environment-1p23r698i9.pdf

Authoritative sources in a hyperlinked environment

Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach. The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package--PMTK (probabilistic modeling toolkit)--that is freely available online. The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students.

Machine Learning : A Probabilistic Perspective

This paper presents the design and evaluation of Pastry, a scalable, distributed object location and routing substrate for wide-area peer-to-peer ap- plications. Pastry performs application-level routing and object location in a po- tentially very large overlay network of nodes connected via the Internet. It can be used to support a variety of peer-to-peer applications, including global data storage, data sharing, group communication and naming. Each node in the Pastry network has a unique identifier (nodeId). When presented with a message and a key, a Pastry node efficiently routes the message to the node with a nodeId that is numerically closest to the key, among all currently live Pastry nodes. Each Pastry node keeps track of its immediate neighbors in the nodeId space, and notifies applications of new node arrivals, node failures and recoveries. Pastry takes into account network locality; it seeks to minimize the distance messages travel, according to a to scalar proximity metric like the number of IP routing hops. Pastry is completely decentralized, scalable, and self-organizing; it automatically adapts to the arrival, departure and failure of nodes. Experimental results obtained with a prototype implementation on an emulated network of up to 100,000 nodes confirm Pastry's scalability and efficiency, its ability to self-organize and adapt to node failures, and its good network locality properties.

/pdf/pastry-scalable-decentralized-object-location-and-routing-1u2equbbbp.pdf

Pastry: Scalable, Decentralized Object Location, and Routing for Large-Scale Peer-to-Peer Systems

This paper describes a longitudinal field experiment in personal note-taking that examines how people capture and use information in short textual notes. Study participants used our tool, a simple browser-based textual note-taking utility, to capture personal information over the course of ten days. We examined the information they kept in notes using the tool, how this information was expressed, and aspects of note creation, editing, deletion, and search. We found that notes were recorded extremely quickly and tersely, combined information of multiple types, and were rarely revised or deleted. The results of the study demonstrate the need for a tool such as ours to support the rapid capture and retrieval of short notes-to-self, and afford insights into how users' actual note-keeping tendencies could be used to better support their needs in future PIM tools.

/pdf/note-to-self-examining-personal-information-keeping-in-a-2y94p7c9it.pdf

Note to self: examining personal information keeping in a lightweight note-taking tool

We introduce a novel algorithm for decoding turbo-like codes based on linear programming. We prove that for the case of repeat-accumulate (RA) codes, under the binary symmetric channel with a certain constant threshold bound on the noise, the error probability of our algorithm is bounded by an inverse polynomial in the code length. Our linear program (LP) minimizes the distance between the received bits and binary variables representing the code bits. Our LP is based on a representation of the code where code words are paths through a graph. Consequently, the LP bears a strong resemblance to the min-cost flow LP. The error bounds are based on an analysis of the probability, over the random noise of the channel, that the optimum solution to the LP is the path corresponding to the original transmitted code word.

Decoding turbo-like codes via linear programming

Scheduling algorithms

http://iswc2007.semanticweb.org/papers/239.pdf

Potluck: Data mash-up tool for casual users

A key feature of relational database applications is managing \emph{plural} relationships---one-to-many and many-to-many---between entities. However, since it is often infeasible to adopt or develop a new database application for any given schema at hand, information workers instead turn to spreadsheets, which lend themselves poorly to schemas requiring multiple related entity sets. In this paper, we propose to reduce the cost-usability gap between spreadsheets and tailor-made relational database applications by extending the spreadsheet paradigm to let the user establish relationships between rows in related worksheets as well as view and navigate the hierarchical cell structure that arises as a result. We present Related Worksheets, a spreadsheet-like prototype application, and evaluate it with a screencast-based user study on 36 Mechanical Turk workers. First-time users of our software were able to solve lookup-type query tasks with the same or higher accuracy as subjects using Microsoft Excel, in one case 40% faster on average.

/pdf/a-spreadsheet-based-user-interface-for-managing-plural-2ptdwzg82i.pdf

David R. Karger

Papers

Note to self: examining personal information keeping in a lightweight note-taking tool

Decoding turbo-like codes via linear programming

Scheduling algorithms

Potluck: Data mash-up tool for casual users

A spreadsheet-based user interface for managing plural relationships in structured data