M. Terry, E. D. Mynatt, K. Ryall, and D. Leigh. Social net: Using patterns of physical proximity over time to infer shared interests. In CHI, editor, Proceedings of the Human Factors in Computing Systems Conference (CHI 2002), Minneapolis, MN, 20–25 April 2002.
—————————————

The core idea of this paper is to infer from proximity people’s common interests. Example: if two people regularly exercise in the same fitness centre, Social Net detects this pattern and assume they share common interests. In addition a set of automated actions is carried out by the agent. For example, Social Net searches in the contact list of the persons “in proximity” and if a common friend is found then this person is suggested to introduce the two friends in common.

Social Net’s core idea is to use patterns an physical proximity over time to infer shared interests:

Social Net is a novel interest-matching application that looks at patterns of collocation over time to infer shared interests between people. When two people are frequently observed near one another, Social Net searches for a mutual friend to introduce the two. In this way, Social Net strikes a balance between the affordances and capabilities of the technology (i.e., the ability to detect long-term trends of collocation between people) and the natural ability for people to mediate interpersonal interactions (e.g., deciding if, when, and how two people should be introduced).

[more…]

Thad Starner is an Assistant Professor in Georgia Tech’s College of Computing, where he founded and directs the Contextual Computing Group. Thad holds four degrees from MIT, including his PhD from the MIT Media Laboratory in 1999. Starner was an Associate Scientist with BBN’s Speech Systems Group in 1993 when he created one of the earliest high-accuracy on-line cursive handwriting recognition systems. Starner is one of the pioneers of wearable computing and has authored over 50 peer-reviewed scientific publications and book chapters in mobile computing, computer vision, augmented environments, and pattern recognition. Starner co-founded the IEEE International Symposium on Wearable Computers (ISWC) and is one of the founding members of the IEEE Technical Committee on the subject. He is also a founder of the MIT Wearable Computing Project and Charmed Technology. His work includes a gloveless, real-time sign language recognizer; various intelligent agents in support of everyday memory; theoretical frameworks for power generation and heat dissipation for wearables; several augmented realities; and a computer-vision based interactive workbench for which he received a “best paper” award at VR2000. Thad’s current work researches the use of computational agents for everyday-use wearable computers.

[more…]

D. Ashbrook and T. Starner. Using gps to learn significant locations and predict movement across multiple users. Personal Ubiquitous Computing, (7):275–286, 2003.
——————————————-

This article shows an interesting approach to predict the user movements registering the user’s position through a GPS. The starting point is that for any technology to be useful the system must have a knowledge of what the user will do, where or when s/he will do it and the reason for the action. –In my case I am looking for the description of the place rather than on the user’s behavior.– The approach they followed is interesting and exemplar, because it is build on simple assumption, which are mainly inferred conjectures: a person who stops for a couple of time at a certain places may have particular interests there, therefore the place is a location. [other examples: stopping time marks the end and starting point of a trip (Wolf); loss of GPS signal is a building (Marmasse)]. On the application side there are several ideas proposed by the authors: spatial to-do-list: associate a task-reminder at a particular location; another may be the task sharing with other peers or the proximity-help-optimization: a friend is near a place you cannot go to pick up something and you ask for help; find people with similar interests based on physical proximity of certain preferential zones (Social Net – Terry). The goal they started with was to find a technique that would automatically pick out patterns in the data that would normally mirror what we observe about human movement. Then they reconsidered to aim for providing some starting inputs into the system that eventually would give some results. Their initial definition of “place” is interesting: any logged GPS coordinate with an interval of time “t” between it and the previous one. In addition they also did something interesting for defining statistically the notion of location and sublocation: they did clustering using a variant of the k-means clustering algorithm. They also used user inputs to enhance the identity of the space for the extent to verify the outcomes of the algorithm with the user’s expectations. The experimental model, though, I found weak. The conclusions is that they proved the possibility to detect space structures but their goal was also to detect time structures. They used a system called GPSVis to log data.

Reading the article about epistomat I found the missing link for my thesis project. Basically the idea is to give the user the ability to validate the ontology defined by the agent so that they collaboratively participate to the social meaning construction. In this process there is also an informal learning.

See the link with the Nomic game.

He is a philosopher, a university teacher and a researcher. He designed the game Nomic. He is also involved with the Open Acess project.

[more …]

Nomic is a game invented in 1982. It’s a game in which changing the rules is a move. The Initial Set of rules does little more than regulate the rule-changing process. While most of its initial rules are procedural in this sense, it does have one substantive rule (on how to earn points toward winning); but this rule is deliberately boring so that players will quickly amend it to please themselves.

[more…]

OWL is an acronym for Web Ontology Language, a markup language for publishing and sharing data using ontologies on the Internet. OWL is a vocabulary extension of RDF (the Resource Description Framework) and is derived from the DAML+OIL Web Ontology Language. Together with RDF and other components, these tools make up the semantic web project.

wikipedia

OpenCyc is the open source version of the Cyc technology, the world’s largest and most complete general knowledge base and commonsense reasoning engine. Cycorp, the builders of Cyc, have set up an independent organization, OpenCyc.org, to disseminate and administer OpenCyc, and have committed to a pipeline through which all current and future Cyc technology will flow into ResearchCyc (available for R&D in academia and industry) and then OpenCyc.

[more …]

In computer science, an ontology is the attempt to formulate an exhaustive and rigorous conceptual schema within a given domain, a typically hierarchical data structure containing all the relevant entities and their relationships and rules (theorems, regulations) within that domain.

wikipedia