Que sais-je?

Technology Review caught up with Pentland to ask him about reality mining and its implications.

Technology Review: When you talk about reality mining, what do you mean?

Sandy Pentland: The real roots of it go back to early 1990s, when people first started talking about context-aware computing. Just look at a cell phone. It knows where you are, and this is obviously sort of useful. But the generalization is that maybe it can know lots of things about you. Take your Facebook friends as an example. The phone could know which ones you socialize with in person, which ones are your work friends, and which friends you've never seen in your life. That's an interesting distinction, and reality mining can make it automatic. It's about making the "dumb" information-technology infrastructure know something about your social life. All this sort-of Web 2.0 stuff is nice, but you have to type stuff in. Things are never up to date, and unless you consciously know about something, you can't put it in. Reality mining is all about paying attention to patterns in life and using that information to help you do things like set privacy policies, share things with people, notify people when you're near them, and just to help you live your life.

TR: What technologies are enabling reality mining now?

SP: Today's cell phones are on us all the time, and they come with hardware that can act as sensors for your environment. For instance, if Bluetooth is turned on, then the phone can see and be seen by other Bluetooth devices. You can start to make a record of the Bluetooth-enabled devices you encounter throughout the day. Then you can figure out, based on the frequency [with which] you encounter other people's Bluetooth phones, what sort of relationship you have with them.

The iPhone also has an accelerometer that could tell if you are sitting and walking. You don't have to explicitly type stuff in; it's just measured. And all phones have built-in microphones that can be used to analyze your tone of voice, how long you talk, how often you interrupt people. These patterns can tell you what roles people play in groups: you can figure out who the leader is and who the followers are. It's folk psychology, and some of the stuff people may already know, but we haven't been able to measure it, at such a large scale, before these phones.

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온톨로지의 어원: 철학의 존재론

존재론: 실재에 대한 정확한 이해를 추구하는 학문이다

실재: 우리의 눈에 보이는 이 세상의 모든 것

존재론 + 실재: 이 세상을 규정하기 위해 세상에 존재하는 실체들에 대한 명확한 이해와 정의를 연구하는 것

온톨로지는 이러한 존재론의 기본 철학을 정보시스템에 적용하여 정보시스템의 대상이 되는 자원의 개념을 명확하게 정의하고 상세하게 기술하여 보다 정확한 정보를 찾을 수 있도록 하는데 목적이 있다.

정보를 효과적으로 관리하고 검색하기 위한 지향점

Tom Gruber: An ontology is a specification of a conceptualization (온톨로지는 개념화의 명세이다.)

개념화: 무언가를 개념으로 만드는 것 즉, 사물이나 추상적으로 존재하는 관념들을 구체적인 집합으로 만드는 것

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Semantic Search
R. Guha  IBM Research, Almaden rguha@us.ibm.com
Rob McCool  Knowledge Systems Lab, Stanford Stanford, CA, USA robm@ksl.stanford.edu
Eric Miller  W3C/MIT Cambridge, MA, USA em@w3.org

2. SEMANTIC SEARCH INTRODUCTION

 Semantic search is an application of the Semantic Web to search.

We believe that the addition of explicit semantics can improve search.

Semantic Search attempts to augment and improve traditional search results (based on Information Retrieval technology) by using data from the Semantic Web.

 Traditional Information Retrieval (IR) technology is based almost purely on the occurrence of words in documents.

Search engines like Google [9]), augment this in the context of the Web with information about the hyperlink structure of the Web.

Navigational Searches: In this class of searches, the user provides the search engine a phrase or combination of words which s/he expects to find in the documents. There is no straightforward, reasonable interpretation of these words as denoting a concept. In such cases, the user is using the search engine as a navigation tool to navigate to a particular intended document.
We are not interested in this class of searches.

예) A search query like “W3C track 2pm Panel” does not denote any concept. The user is likely just trying to find the page containing all these words.

Research Searches: In many other cases, the user provides the search engine with a phrase which is intended to denote an object about which the user is trying to gather/research information. There is no particular document which the user knows about that s/he is trying to get to. Rather, the user is trying to locate a number of documents which together will give him/her the information s/he is trying to find. This is the class of searches we are interested in.

예) search queries like “Eric Miller” or “Dublin Ohio”, denote a person or a place. The user is likely doing an research search on the person or place denoted by the query.

We have built two Semantic Search systems. The first system, Activity Based Search (ABS), provides Semantic Search for a range
of domains, including musicians, athletes, actors, places and products.
The second system (W3C Semantic Search) is more focused and provides Semantic Search for the website of the World Wide Web Consortium (http://www.w3.org/).

 Both the Semantic Search application and these portions of the Semantic Web have been built on top of the TAP infrastructure.

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