Inspired by empirical studies of networked systems such as the Internet, social networks, and biological networks, researchers have in recent years developed a variety of techniques and models to help us understand or predict the behavior of these systems. Here we review developments in this field, including such concepts as the small-world effect, degree distributions, clustering, network correlations, random graph models, models of network growth and preferential attachment, and dynamical processes taking place on networks.

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The Structure and Function of Complex Networks

This paper presents an overview of the field of recommender systems and describes the current generation of recommendation methods that are usually classified into the following three main categories: content-based, collaborative, and hybrid recommendation approaches. This paper also describes various limitations of current recommendation methods and discusses possible extensions that can improve recommendation capabilities and make recommender systems applicable to an even broader range of applications. These extensions include, among others, an improvement of understanding of users and items, incorporation of the contextual information into the recommendation process, support for multicriteria ratings, and a provision of more flexible and less intrusive types of recommendations.

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Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions

As the Netflix Prize competition has demonstrated, matrix factorization models are superior to classic nearest neighbor techniques for producing product recommendations, allowing the incorporation of additional information such as implicit feedback, temporal effects, and confidence levels

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Matrix Factorization Techniques for Recommender Systems

Recommender systems apply knowledge discovery techniques to the problem of making personalized recommendations for information, products or services during a live interaction. These systems, especially the k-nearest neighbor collaborative ltering based ones, are achieving widespread success on the Web. The tremendous growth in the amount of available information and the number of visitors to Web sites in recent years poses some key challenges for recommender systems. These are: producing high quality recommendations, performing many recommendations per second for millions of users and items and achieving high coverage in the face of data sparsity. In traditional collaborative ltering systems the amount of work increases with the number of participants in the system. New recommender system technologies are needed that can quickly produce high quality recommendations, even for very large-scale problems. To address these issues we have explored item-based collaborative ltering techniques. Item-based techniques rst analyze the user-item matrix to identify relationships between di erent items, and then use these relationships to indirectly compute recommendations for users. In this paper we analyze di erent item-based recommendation generation algorithms. We look into di erent techniques for computing item-item similarities (e.g., item-item correlation vs. cosine similarities between item vectors) and di erent techniques for obtaining recommendations from them (e.g., weighted sum vs. regression model). Finally, we experimentally evaluate our results and compare them to the basic k-nearest neighbor approach. Our experiments suggest that item-based algorithms provide dramatically better performance than user-based algorithms, while at the same time providing better quality than the best available userbased algorithms.

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Item-based collaborative filtering recommendation algorithms

PROBLEM TO BE SOLVED: To solve the problem, wherein it is impossible for an electronic content information provider to provide commercially secure and effective method, for a configurable general-purpose electronic commercial transaction/distribution control system. SOLUTION: In this system, having at least one protected processing environment for safely controlling at least one portion of decoding of digital information, a secure content distribution method comprises a process for encapsulating digital information in one or more digital containers; a process for encrypting at least a portion of digital information; a process for associating at least partially secure control information for managing interactions with encrypted digital information and/or digital container; a process for delivering one or more digital containers to a digital information user; and a process for using a protected processing environment, for safely controlling at least a portion of the decoding of the digital information. COPYRIGHT: (C)2006,JPO&NCIPI

https://apps.dtic.mil/dtic/tr/fulltext/u2/a423264.pdf

Systems and Methods for Secure Transaction Management and Electronic Rights Protection

The Tapestry experimental mail system developed at the Xerox Palo Alto Research Center is predicated on the belief that information filtering can be more effective when humans are involved in the filtering process. Tapestry was designed to support both content-based filtering and collaborative filtering, which entails people collaborating to help each other perform filtering by recording their reactions to documents they read. The reactions are called annotations; they can be accessed by other people’s filters. Tapestry is intended to handle any incoming stream of electronic documents and serves both as a mail filter and repository; its components are the indexer, document store, annotation store, filterer, little box, remailer, appraiser and reader/browser. Tapestry’s client/server architecture, its various components, and the Tapestry query language are described.

Using collaborative filtering to weave an information tapestry

In a database to which data is continually added, users may wish to issue a permanent query and be notified whenever data matches the query. If such continuous queries examine only single records, this can be implemented by examining each record as it arrives. This is very efficient because only the incoming record needs to be scanned. This simple approach does not work for queries involving joins or time. The Tapestry system allows users to issue such queries over a database of mail and bulletin board messages. The user issues a static query, such as “show me all messages that have been replied to by Jones,” as though the database were fixed and unchanging. Tapestry converts the query into an incremental query that efficiently finds new matches to the original query as new messages are added to the database. This paper describes the techniques used in Tapestry, which do not depend on triggers and thus be implemented on any commercial database that supports SQL. Although Tapestry is designed for filtering mail and news messages, its techniques are applicable to any append-only database.

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Continuous queries over append-only databases

In a network, a media coordination system provides secure multimedia communication channels in a collaborative network environment. The media coordination system provides automatic encryption, dynamic interconnection of streams of data, and user interface elements that provide users with control over the ultimate destination of their audio and video data. The infrastructure of the system includes a plurality of client workstations that are connected to a central server using point-to-point network connections. The central server maintains a persistent virtual world of network places with objects located therein. Streams of audio and video data are coordinated between client workstations operating in the persistent virtual world by a key manager object using channels, transmitters, and receivers. The client workstations multicast their audio and video data over the network to defined recipients after receiving a multicast address and an encryption key for a specific multicast channel. In order to protect the privacy of all communications and the integrity of the coordination system, each client workstation retains significant control over distribution and reception of audio and video data since multicast transmission is tied to specific user interface elements. The multimedia user interface elements include cameras, speakers, microphones, and video panes. Since the central server only coordinates where audio and video data is broadcast for a particular interface element, each client workstation ultimately controls the destination of multimedia data through selection of the element at the user interface.

Multimedia coordination system

A method in which access control programs (ACPs) permit controlled delegation of access rights from clients to untrusted intermediaries. ACPs are programs that encode arbitrary specifications of delegated access rights. In the method, a client creates an ACP and associates it with a request to a server, the request being made through one or more intermediaries. When processing a request received from an intermediary, the server executes the access control program to determine whether or not to grant the request.

Method for delegating access rights through executable access control program without delegating access rights not in a specification to any intermediary nor comprising server security

Jupiter is a multi-user, multimedia virtual world intended to support long-term remote collaboration. In particular, it supports shared documents, shared tools, and, optionally, live audio/video communication. Users who program can, with only moderate effort, create new kinds of shared tools using a high-level windowing toolkit; the toolkit provides transparent support for fully-shared widgets by default. This paper describes the low-level communications facilities used by the implementation of the toolkit to enable that support. The state of the Jupiter virtual world, including application code written by users, is stored and (for code) executed in a central server shared by all of the users. This architecture, along with our desire to support multiple client platforms and high-latency networks, led us to a design in which the server and clients communicate in terms of high-level widgets and user events. As in other groupware toolkits, we need a concurrency-control algorithm to maintain common values for all instances of the shared widgets. Our algorithm is derived from a fully distributed, optimistic algorithm developed by Ellis and Gibbs [12]. Jupiter’s centralized architecture allows us to substantially simplify their algorithm. This combination of a centralized architecture and optimistic concurrency control gives us both easy serializability of concurrent update streams and fast response to user actions. The algorithm relies on operation transformations to fix up conflicting messages. The best transformations are not always obvious, though, and several conflicting concerns are involved in choosing them. We present our experience with choosing transformations for our widget set, which includes a text editor, a graphical drawing widget, and a number of simpler widgets such as buttons and sliders.

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David A. Nichols

Papers

Using collaborative filtering to weave an information tapestry

Continuous queries over append-only databases

Multimedia coordination system

Method for delegating access rights through executable access control program without delegating access rights not in a specification to any intermediary nor comprising server security

High-latency, low-bandwidth windowing in the Jupiter collaboration system