collaborative filtering

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Comprehensive Analysis of Web Privacy and Anonymous Web Browsers: Are Next Generation Services Based on Collaborative Filtering?

In general, networking privacy enhancing technologies are better on larger user bases - such criteria that can be enhanced by combining them with community based services. This paper presents main web privacy issues and today's complex preventive solutions, anonymous web browsers, in several aspects including a comprehensive taxonomy as a...

Tags: Web, Privacy, Web Browser, Analysis, Collaborative Filtering, Web Browsers, Internet

White papers 2008-06-24

Collaborative Filtering on Skewed Datasets

Many real life datasets have skewed distributions of events when the probability of observing few events far exceeds the others. This paper observed that in skewed datasets the state of the art collaborative filtering methods perform worse than a simple probabilistic model. The test bench includes a real ad click...

Tags: Collaborative Filtering, Test Bench

White papers 2008-05-21

Youlicit 1 (Windows)

Youlicit's underlying premise is that of reducing information overload using collaborative filtering. We gather data from our users as well as other sources of user annotated web data (from social bookmarking sites such as Del.icio.us, other collaborative filtering sites such as Digg and Amazon, "people-generated" classifications of sites, and a...

Tags: Social Bookmarking, Microsoft Windows, Collaborative Filtering, Youlicit

Software downloads 2007-10-03

Collaborative filtering: comparing Reddit's karma system to Digg

In recent weeks I've given Digg.com a bit of coverage, albeit of the kind they wouldn't have enjoyed. But actually I love the concept of digg.com and I still think it has a lot of potential, as long as they reduce the groupthink and address the spam issues (which to...

Tags: Digg, Reddit

Blog posts 2006-01-16

A Fuzzy Hybrid Collaborative Filtering Technique for Web Personalization

Collaborative filtering CF is a popular technique used in web personalization for building recommender systems, which predict the preferences of an active user, based on the preferences of past like-minded users. CF techniques are either memory- based or model-based. While the former is more accurate, its scalability compared to model-based...

Tags: Technique, Web, Personalization, Collaborative Filtering, Collaborative Filtering Technique, Productivity

White papers 2005-08-01

Social Semantic Collaborative Filtering

Social Semantic Collaborative Filtering enhances knowledge sharing through communities. It delivers community-oriented, semantically-rich taxonomies, information about a user's interest and flows of expertise from the domain expert.

Tags: Collaborative Filtering, Digital Enterprise Research Institute

Presentations

Additional Resources

Salesforce Chatter: what a clanger!

Running Cover-it-Live has produced some interesting commentary about this morning's announcement of Salesforce.com Chatter. Best summed up by Nenshad Bardoliwalla: The length of this keynote has turned "Chatter" into "Splatter" IMHO A three and a quarter hour keynote marathon, laced with the kind of hyperbole we've come to...

Tags: Salesforce.com Inc., Marc Benioff, Running Cover-it-Live, Saesforce.com, Sales Force Management, Sales, Dennis Howlett

Blog posts 2009-11-18

News to know: Win7, Google Wave, Palm WebOS, Apple Tablet, Google Docs

Here are today's notable headlines. You can get News To Know via email alert and RSS daily. For continuous updates see BNET's around-the-Web tech coverage. Mary Jo Foley: Microsoft's message to IT pros: Meet us half way with Windows 7 Larry Dignan: ...

Tags: Tom Foremski, Google Inc., Larry Dignan, Google Docs, Palm Inc., Andrew Nusca, Apple Inc., Microsoft Corp., Matthew Miller, Adrian Kingsley-Hughes, Microsoft Windows 7, Microsoft Windows, Tablets, Sales Strategy, Operating Systems, Software, Hardware, Notebooks & Tablets, Sales, Sam Diaz

Blog posts 2009-09-30

Symbolic Data Analysis Tools for Recommendation Systems

Recommendation Systems have become an important tool to cope with the information overload problem by acquiring data about the user behavior. After tracing the user behavior, through actions or rates, Computational Recommendation Systems use information filtering techniques to recommend items. In order to recommend new items, one of the three...

Tags: User Behavior, Data Analysis, Method

White papers 2009-04-22

Building a virtual B2B user community

* Jennifer Leggio is at RSA Conference Guest editorial by Joel Lundgren I was first introduced to Facebook in the summer of 2007. At that time most people in Sweden had yet to hear about this site, and the idea that it had anything...

Tags: Community, Customer, Joel Lundgren, openIFS, Lundgren, Blogging, B2B, Branding, Internet, E-business/E-Commerce, Marketing, Jennifer Leggio

Blog posts 2009-04-21

Web Spam Filtering in Internet Archives

While Web spam is targeted for the high commercial value of top-ranked search-engine results, Web archives observe quality deterioration and resource waste as a side effect. So far Web spam filtering technologies are rarely used by Web archivists but planned in the future as indicated in a survey with responses...

Tags: Web, Spam Filtering, Channel Management, Internet, Marketing

White papers 2009-04-21

Using Co-Presence Communities to Enhance Social Recommendation

This paper proposes a social recommendation algorithm for use in a research social network environment. The social recommendation algorithm proposed combines the concepts of a relationship ontology and item-based Collaborative Filtering CF. While the network setup in social networking sites can accurately reflect the social landscape of its users, it...

Tags: Co-presence Community, Recommendation Algorithm, Social Networking, Online Communications, Marketing, Advertising & Promotion

White papers 2009-04-10

Message Sniffer 3.0 (Windows)

Message Sniffer is an advanced anti-spam filter for ISPs, network security providers, and business e-mail systems. The engine uses advanced pattern recognition, machine learning, and adaptive IP Reputation technologies to accurately identify spam and other e-mail borne malware. The cross-platform, high performance engine runs on Windows, Linux and BSD systems....

Tags: Server, Microsoft Windows, Engine, E-mail, Linux, Online Communications, Operating Systems, Software

Software downloads 2009-04-01

Knowledge Plaza: Sophisticated Knowledge Workspace

There are various shades, strengths and weaknesses to competing software packages, with vendors catering to different user segments and market success often defining the direction of their products. Knowledge Plaza is a relatively new offering in the enterprise collaboration space and offers a...

Tags: Knowledge, Knowledge Plaza, Searches, Strategy, Management, Oliver Marks

Blog posts 2009-02-13

Artificial Immune System for Collaborative Spam Filtering

Artificial Immune Systems AIS use the concepts and algorithms inspired by the theory of how the human immune system works. This paper presents the design and initial evaluation of a new artificial immune system for collaborative spam filtering. Collaborative spam filtering allows for the detection of not-previously-seen spam content, by...

Tags: Spam Filtering, Spam, Viruses And Worms, Security, Spam And Phishing

White papers 2008-11-10

The Business Resource Planning Farm League

The enterprise juggernauts in the Enterprise resource planning ERP space are duking it out in rapidly changing business conditions - SAP are offering packages of applications with zero percent financing, Oracle are on the acquisition trail, buying regulatory compliance rules company Haley, their tenth buy this...

Tags: Intuit Inc., Intuit QuickBase, Small Business, Productivity, Taxes, Smb/Sme, Financial Planning, Finance, Oliver Marks

Blog posts 2008-11-08

Resolving FP-TP Conflict in Digest-Based Collaborative Spam Detection by Use of Negative Selection Algorithm

A well-known approach for collaborative spam filtering is to determine which emails belong to the same bulk, e.g. by exploiting their content similarity. This allows, after ob-serving an initial portion of a bulk, for the bulkiness scores to be assigned to the remaining emails from the same bulk. This also...

Tags: Algorithm, Bulk, E-mail, Online Communications

White papers 2008-08-22

Two flavors of software as a service: Intuit QuickBase and Etelos

There are dozens of flavors of clever applications aimed at the office productivity market, often spawned as a result of the Web 2.0 explosion. Where the Web 2.0 application market is driven by eyeballs and their resulting advertising monetization, the enterprise 2.0...

Tags: Security, Software-as-a-service, Intuit Inc., Intuit QuickBase, Etelos, Developer Platform, Software As A Service (SaaS), Cloud Computing, Collaboration, Emerging Technologies, Oliver Marks

Blog posts 2008-08-14

One-Class Collaborative Filtering

Many applications of Collaborative Filtering CF, such as news item recommendation and bookmark recommendation, are most naturally thought of as One-Class Collaborative Filtering OCCF problems. In these problems, the training data usually consist simply of binary data reflecting a user's action or inaction, such as page visitation in the case...

Tags: Training, Workforce Management, Training And Certification, Human Resources

White papers 2008-07-16

Improving Digest-Based Collaborative Spam Detection

Spam is usually sent in bulk. A bulk mailing consists of many copies of the same original spam message, each sent to a different recipient. The copies are usually obfuscated, i.e. modified a bit in order to look different from each other. In collaborative spam filtering it is important to...

Tags: Bulk, EPFL, E-mail, Online Communications

White papers 2008-03-28