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

Social network sites SNSs are increasingly attracting the attention of academic and industry researchers intrigued by their affordances and reach This special theme section of the Journal of Computer-Mediated Communication brings together scholarship on these emergent phenomena In this introductory article, we describe features of SNSs and propose a comprehensive definition We then present one perspective on the history of such sites, discussing key changes and developments After briefly summarizing existing scholarship concerning SNSs, we discuss the articles in this special section and conclude with considerations for future research

https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1083-6101.2007.00393.x

Social Network Sites: Definition, History, and Scholarship

https://www2.econ.iastate.edu/tesfatsi/DeepLearningInNeuralNetworksOverview.JSchmidhuber2015.pdf

Deep learning in neural networks

Background on genetic algorithms, LISP, and genetic programming hierarchical problem-solving introduction to automatically-defined functions - the two-boxes problem problems that straddle the breakeven point for computational effort Boolean parity functions determining the architecture of the program the lawnmower problem the bumblebee problem the increasing benefits of ADFs as problems are scaled up finding an impulse response function artificial ant on the San Mateo trail obstacle-avoiding robot the minesweeper problem automatic discovery of detectors for letter recognition flushes and four-of-a-kinds in a pinochle deck introduction to biochemistry and molecular biology prediction of transmembrane domains in proteins prediction of omega loops in proteins lookahead version of the transmembrane problem evolutionary selection of the architecture of the program evolution of primitives and sufficiency evolutionary selection of terminals evolution of closure simultaneous evolution of architecture, primitive functions, terminals, sufficiency, and closure the role of representation and the lens effect Appendices: list of special symbols list of special functions list of type fonts default parameters computer implementation annotated bibliography of genetic programming electronic mailing list and public repository

Genetic Programming: On the Programming of Computers by Means of Natural Selection

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

This paper describes a technique for making personalized recommendations from any type of database to a user based on similarities between the interest profile of that user and those of other users. In particular, we discuss the implementation of a networked system called Ringo, which makes personalized recommendations for music albums and artists. Ringo's database of users and artists grows dynamically as more people use the system and enter more information. Four different algorithms for making recommendations by using social information filtering were tested and compared. We present quantitative and qualitative results obtained from the use of Ringo by more than 2000 people.

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Social information filtering: algorithms for automating “word of mouth”

Publisher Summary Computers are becoming the vehicle for an increasing range of everyday activities. Acquisition of news and information, mail and even social interactions and entertainment have become more and more computer based. These technological developments are not in line with a change in the way people interact with computers. Techniques from the field of AI, in particular so-called autonomous agents, can be used to implement a complementary style of interaction, which has been referred to as indirect management. Agents assist users in a range of different ways. They hide the complexity of difficult tasks, they perform tasks on the user's behalf, they can train or teach the user, they help different users collaborate, and they monitor events and procedures. The chapter focuses on an approach to building interface agents. It presents results from several prototype agents that have been built using this approach, including agents that provide personalized assistance with meeting scheduling, email handling, electronic news filtering, and selection of entertainment.

Agents that reduce work and information overload

This paper brings some perspective to various concepts in computational reflection. A definition of computational reflection is presented, the importance of computational reflection is discussed and the architecture of languages that support reflection is studied. Further, this paper presents a survey of some experiments in reflection which have been performed. Examples of existing procedural, logic-based and rule-based languages with an architecture for reflection are briefly presented. The main part of the paper describes an original experiment to introduce a reflective architecture in an object-oriented language. It stresses the contributions of this language to the field of object-oriented programming and illustrates the new programming style made possible. The examples show that a lot of programming problems that were previously handled on an ad hoc basis, can in a reflective architecture be solved more elegantly.

Concepts and experiments in computational reflection

While there are many Web services which help users find things to buy, we know of none which actually try to automate the process of buying and selling. Kasbah is a system where users create autonomous agents to buy and sell goods on their behalf. In this paper, we describe how Kasbah works. We also discuss the implementation of a simple proof-of-concept prototype.

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Kasbah: An Agent Marketplace for Buying and Selling Goods

COMMUNICATIONS OF THE ACM March 1999/Vol. 42, No. 3 81 However, the potential of the Internet for transforming commerce is largely unrealized. Electronic purchases are still largely nonautomated. While information about products and vendors is more easily accessible, and orders and payments are dealt with electronically, humans are still in the loop in all stages of the buying process, adding to transaction costs. A human buyer is still responsible for collecting and interpreting information on merchants and products, making decisions about merchants and products, and ultimately entering purchase and payment information. Software agent technologies can be used to automate several of the most time-consuming stages of the buying process. Unlike socalled traditional software, software agents are personalized, continuously running, and semiautonomous [1]. These qualities help optimize the whole buying experience, revolutionizing commerce as we know it [2]. For example, a company that needs to opular software agents were first used several years

Pattie Maes

Papers

Social information filtering: algorithms for automating “word of mouth”

Agents that reduce work and information overload

Concepts and experiments in computational reflection

Kasbah: An Agent Marketplace for Buying and Selling Goods

Agents that buy and sell