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심장이 두근거리고 밤에 꿈에서도 간절히 만나는 그러한 희망을 꿈꾸고 있습니다. 이 절실한 꿈을 위해 인내할 수 있습니다. 이 절실한 꿈을 위해 기다릴 수 있습니다. 당당하게 미래를 바라봅니다. 가슴은 미래를 향해, 그리고 나의 손과 발은 현재를 열심히 가꾸고 있습니다.
by cykaneys
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  1. 2008/04/26
    Enriching the Connections of the Web -- Making the Web Smarter
  2. 2008/04/25
    [펌] 시멘틱웹과 서비스, 그리고 온톨로지 - #1 온톨로지
  3. 2008/04/25
    시멘틱 웹이란 ?
  4. 2008/04/25
    Semantic Web: What Is The Killer App?
  5. 2008/04/25
    2008 Web Predictions
  6. 2008/04/23
    성공을 위한 10계명
  7. 2008/04/23
    리더가 갖추어야 할 기본자세는 어떠해야 될까?
  8. 2008/04/21
    가트너 10대 혁신기술 선정
  9. 2008/04/21
    mashup이란
  10. 2008/04/21
    세컨드 라이프에서의 비즈니스 성공비밀

Enriching the Connections of the Web -- Making the Web Smarter

Web 3.0 -- aka The Semantic Web -- is about enriching the connections of the Web. By enriching the connections within the Web, the entire Web may become smarter.

I  believe that collective intelligence primarily comes from connections -- this is certainly the case in the brain where the number of connections between neurons far outnumbers the number of neurons; certainly there is more "intelligence" encoded in the brain's connections than in the neurons alone. There are several kinds of connections on the Web:

  1. Connections between information (such as links)
  2. Connections between people (such as opt-in social relationships, buddy lists, etc.)
  3. Connections between applications (web services, mashups, client server sessions, etc.)
  4. Connections between information and people (personal data collections, blogs, social bookmarking, search results, etc.)
  5. Connections between information and applications (databases and data sets stored or accessible by particular apps)
  6. Connections between people and applications (user accounts, preferences, cookies, etc.)

Are there other kinds of connections that I haven't listed -- please let me know!

I believe that the Semantic Web can actually enrich all of these types of connections, adding more semantics not only to the things being connected (such as representations of information or people or apps) but also to the connections themselves.

In the Semantic Web approach, connections are represented with statements of the form (subject, predicate, object) where the elements have URIs that connect them to various ontologies where their precise intended meaning can be defined. These simple statements are sometimes called "triples" because they have three elements. In fact, many of us are working with statements that have more than three elements ("tuples"), so that we can represent not only subject, predicate, object of statements, but also things like provenance (where did the data for the statement come from?), timestamp (when was the statement made), and other attributes. There really is no limit to what kind of metadata can be stored in these statements. It's a very simple, yet very flexible and extensible data model that can represent any kind of data structure.

The important point for this article however is that in this data model rather than there being just a single type of connection (as is the case on the present Web which basically just provides the HREF hotlink, which simply means "A and B are linked" and may carry minimal metadata in some cases), the Semantic Web enables an infinite range of arbitrarily defined connections to be used.  The meaning of these connections can be very specific or very general.

For example one might define a type of connection called "friend of" or a type of connection called "employee of" -- these have very different meanings (different semantics) which can be made explicit and also machine-readable using OWL. By linking a page about a person with the "employee of" link to another page about a different person, we can express that one of them employs the other. That is a statement that any application which can read OWL is able to see and correctly interpret, by referencing the underlying definition of "employee of" which is defined in some ontology and might for example specify that an "employee of" relation connects a person to a person or organization who is their employer. In other words, rather than just linking things with the generic "hotlink" we are all used to, they can now be linked with specific kinds of links that have very particular and unambiguous meaning and logical implications.

This has the potential at least to dramatically enrich the information-carrying capacity of connections (links) on the Web. It means that connections can carry more meaning, on their own. It's a new place to put meaning in fact -- you can put meaning between things to express their relationships. And since connections (links) far outnumber objects (information, people or applications) on the Web, this means we can radically improve the semantics of the structure of the Web as a whole -- the Web can become more meaningful, literally. This makes a difference, even if all we do is just enrich connections between gross-level objects (in other words, connections between Web pages or data records, as opposed to connections between concepts expressed within them, such as for example, people and companies mentioned within a single document).

Even if the granularity of this improvement in connection technology is relatively gross level it could still be a major improvement to the Web. The long-term implications of this have hardly been imagined let alone understood -- it is analogous to upgrading the dendrites in the human brain; it could be a catalyst for new levels of computation and intelligence to emerge.

It is important to note that, as illustrated above, there are many types of connections that involve people. In other words the Semantic Web, and Web 3.0, are just as much about people as they are about other things. Rather than excluding people, they actually enrich their relationships to other things. The Semantic Web, should, among other things, enable dramatically better social networking and collaboration to take place on the Web. It is not only about enriching content.

Now where will all these rich semantic connections come from? That's the billion dollar question. Personally I think they will come from many places: from end-users as they find things, author content, bookmark content, share content and comment on content (just as hotlinks come from people today), as well as from applications which mine the Web and automatically create them. Note that even when Mining the Web a lot of the data actually still comes from people -- for example, mining the Wikipedia, or a social network yields lots of great data that was ultimately extracted from user-contributions. So mining and artificial intelligence does not always imply "replacing people" -- far from it! In fact, mining is often best applied as a means to effectively leverage the collective intelligence of millions of people.

These are subtle points that are very hard for non-specialists to see -- without actually working with the underlying technologies such as RDF and OWL they are basically impossible to see right now. But soon there will be a range of Semantically-powered end-user-facing apps that will demonstrate this quite obviously. Stay tuned!

Of course these are just my opinions from years of hands-on experience with this stuff, but you are free to disagree or add to what I'm saying. I think there is something big happening though. Upgrading the connections of the Web is bound to have a significant effect on how the Web functions. It may take a while for all this to unfold however. I think we need to think in decades about big changes of this nature.

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프로젝트의 특성상 한참을 프레임워크에 매달려오다가, 정말 최근에 들어서야 시선이 넓어지기 시작했다. 그동안 웹 2.0이니 뭐니 하는 그런 추세들을 모르는 척 한 건 아니지만, 뭔가 절실하고 구체적으로 그림이 그려질랑말랑하는, 그런 말랑말랑한 생각들이 이제야 들기 시작한 것이다. 말랑말랑, 어감이 좋은데?

그런고로, 생각을 정리하는 차원에서 3부에 걸쳐 이런 저런 이야기를 풀어볼까 한다. 어렵게 생각하면 어렵고, 쉽게 생각하면 쉬우니까 글이 길어도 부담 갖지 말고 그냥 쭈욱 읽어 내려가자. 혹시나 문서 끝까지 읽은 사람이 있으면 질문을 던져도 좋다. 피터지게 공부해서 답해줄 생각이다. (나도 잘 모르거든, 그래서 공부해야 답할 수 있다) 잘못된 부분에 대한 지적은 다소 부드러운 어조로 해줬으면 좋겠다. (나는 섬세하니까)


#1 온톨로지(Ontology)



아주 오래전부터 온톨로지라는 영역이 연구되어왔다. 존재론 쯤으로 해석하면 이건 뭐 돈 많고 시간이 남아돌던 부르조아 시대까지 거슬러 올라가겠지만, 컴퓨터 영역으로 한정하면 그렇게까지 거슬러 올라갈 필요는 없을 듯 싶다. 1913년, Webster's Revised Unabridged Dictionary는 온톨로지를 다음과 같이 정의했다.

That department of the science of metaphysics which investigates and explains the nature and essential properties and relations of all beings, as such, or the principles and causes of being.

철학적으로 접근한 이러한 정의는 이후 knowledge engineering, natural-language processing과 같은 인공지능 분야에서 채용하였고 1990년 후반에 들어서면서 intelligent information integration, information retrieval on the Internet, knowledge management 등으로 그 영역이 확장되었다.

인공지능 분야에서 온톨로지는 지식의 공유와 재사용을 목적으로 만들어진다. 이 분야에서 온톨로지는 여러 사람에 의해 다양하게 정의되었는데, 특히 Gruber는 온톨로지를 다음과 같이 소개했다.

An ontology is a formal explicit specification of a shared conceptualization.

온톨로지는 공유되는 개념에 대한 형식적이고 명시적인 명세이다. 공유를 목적으로 하기 때문에 그것은 밖으로 도출(explicit)되어야 하고, 그것을 알아보려면 어떤 형식(formal)을 갖추어야 한다. 그러한 명세(specification)를 온톨로지라고 부른다. 다음은 간단한 온톨로지의 예이다.



온톨로지는 스키마와 인스턴스로 구분해서 생각해 볼 수 있다. 스키마는 위의 그림에서 동그라미로 정의된 어떤 '체계'를 정의한다. 인스턴스는 이렇게 정의된 체계 내에서 실제로 존재하는 '무엇'을 나타낸다. 위의 그림에서 네모로 그려진 [Peter]는 Peter라는 사람을 정의하고 있다. [Peter]는 단순한 데이터에 불과하다. 그러나 이것이 스키마와 결합되면 Peter는 'PhD-Student이고, Student이면서 Reseacher이고, Person이다'라는 정보를 추론할 수 있다. 단지 Peter에 대해 서술한 데이터로부터 (그 자체만으로는 고작 Peter의 나이나 주소 쯤 적혀있었을텐데) 스키마를 통해 명시적으로 서술하지 않은 정보를 얻어냈다. 이것을 추론(inference)이라고 한다.

그래, 그래서 어쩌라고?

좋은 질문이다. 수많은 어플리케이션은 자체적으로 데이터를 관리한다. 데이터베이스를 이용하든, 파일을 이용하든, 메모리를 이용하든, 어떤 방법으로 간에 그것들은 자체적으로 데이터를 관리한다. 문제는 어플리케이션들이 자체적으로 관리하는 데이터가 상호 호환성이 전혀 없다는 것이다. 엔터프라이즈 환경에서 규모가 꽤 큰 쇼핑몰 두 곳을 통합하려할 때, 상호간의 호환성이 전혀 없기에 개발자는 아주 미친듯이 둘 사이를 이어주려고 막코딩을 하거나 데이터베이스를 다시 설계해서 두 곳의 데이터를 통합하려 들 것이다. 어느 세월에...

만약 두 어플리케이션이 (사람)이라는 개념을 정의하고 그에 대한 인스턴스로 고객을 관리했다면 어떨까? 분명 A 쇼핑몰과 B 쇼핑몰은 (사람)이라는 개념을 다르게 표현할 수도 있다. 그래도 같은 개념을 정의한 것이므로 두 개념간의 관계를 정의하면 상호 데이터는 호환이 가능해진다. 예를 들어보자.

쇼핑몰 A는 (사람)이라는 개념을 http://A.com#Person이라고 정의한다. Person은 속성으로 name을 갖는다. 반면 쇼핑몰 B는 (사람)이라는 개념을 http://B.com#Human이라고 정의한다. Human은 속성으로 name과 age를 갖는다.

두 쇼핑몰의 데이터를 통합하려하는데 Person과 Human이 동일하다는 것을 알았다. 일부 속성의 누락은 발생하지만 같은 개념을 표현하고 있다. 따라서 다음과 같은 스키마를 추가할 수 있다.


자 이제 A 쇼핑몰의 어플리케이션이 Person을 검색하면 기존의 Person 데이터 뿐만 아니라 추론을 통해 Human 데이터를 얻을 수 있다.

애초에 두 쇼핑몰이 잘 정의된 (사람)이라는 개념을 채용했다면 통합은 훨씬 수월했을 것이다. 그러나 그렇지 않은 경우라도 두 개념 사이를 잇는 스키마를 추가하는 것으로 데이터의 통합을 이룰 수 있다. 예를 하나 더 들어보자.

얼토당토 않게도, 이 기업은 학원 C를 인수했다. 학원 C는 학생과 강사의 데이터를 정의하는데 (학생)이라는 개념은 http://C.com#Student 로, (강사)라는 개념은 http://C.com#Teacher 로 정의했다. 가만히 보니 학생과 강사는 모두 사람이다. 따라서 다음과 같은 스키마를 추가할 수 있다.


이제 쇼핑몰 A는 Person을 검색하면 그 결과로(추론을 통해) 학원 C의 학생과 강사를 모두 얻을 수 있다. sub-class-of 관계는 is-a 관계로 해석할 수 있다. 추론 과정은 'Student와 Teacher는 Person이다'라고 판단할 수 있게된 것이다. 쇼핑몰 B가 Human을 검색하면 어떨까? 추론 과정은 'Student와 Teacher는 Person이고, Human은 Person과 같은 개념이다'라고 판단 할 수 있으므로 그 결과 학원 C의 학생과 강사를 모두 얻을 수 있다.

어째 고객을 대상으로하는 데이터를 예로 들다보니 'explicit'을 설명하기 꺼려진다. 'explicit' 하다는 것은, 데이터를 시스템 내부에 꽁꽁 숨겨두는 대신, 겉으로 드러내겠다는 것이다. 하지만 이것은 누구나 데이터를 열람할 수 있다는 것을 의미하지는 않는다. 다만, 열람 권한이 있는 대상이 이 데이터에 접근할 수 있고, 그 데이터를 해석할 수 있음을 뜻한다. 해석을 위해서는 서로 이해할 수 있는 잘 정의된 문법 체계를 갖추어야 하며, 그래서 온톨로지의 정의가 'formal'을 포함하는 것이다.

온톨로지를 정의하기 위한 formal한 방법은 여러가지가 있는데 대표적으로 RDF(http://www.w3.org/RDF)와 OWL(http://www.w3.org/2004/OWL)이 있다. 웹 2.0에 관심이 많은 사람이라면 RDF 정도는 들어봤을 듯 싶다. RSS 1.0 스펙이 RDF를 기반으로 작성됐으며, 내 블로그는 안타깝게도 RSS 2.0을 지원하므로 볼 수 없지만 네이버 블로그 같은 곳에 잘 찾아보면 RSS 1.0 버튼이 있을 것이다. 클릭해서 소스를 봐라. (블로그)라는 개념이 어떻게 정의되는지 한 번 보는 것도 그리 나쁘지 않을 것이다.


참고문헌: Jos de Bruijin, Using Ontologies, DERI
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시멘틱 웹 [semantic web] 

컴퓨터가 정보자원의 뜻을 이해하고, 논리적 추론까지 할 수 있는 차세대 지능형 웹.

현재의 컴퓨터처럼 사람이 마우스나 키보드를 이용해 원하는 정보를 찾아 눈으로 보고 이해하는 웹이 아니라, 컴퓨터가 이해할 수 있는 웹을 말한다. 즉 사람이 읽고 해석하기에 편리하게 설계되어 있는 현재의 웹 대신에 컴퓨터가 이해할 수 있는 형태의 새로운 언어로 표현해 기계들끼리 서로 의사소통을 할 수 있는 지능형 웹이다.

원리는 사람들이 이해할 수 있도록 자연어 위주로 되어 있는 현재의 웹 문서와 달리, 정보자원들 사이에 연결되어 있는 의미를 컴퓨터가 이해할 수 있는 형태의 언어로 바꾸는 것이다. 이렇게 되면 컴퓨터가 정보자원의 뜻을 해석하고, 기계들끼리 서로 정보를 주고받으면서 자체적으로 필요한 일을 처리하는 것이 가능해진다.

2004년 현재 시멘틱 웹과 관련된 연구는 RDF(Resource Description Framework)를 기반으로 한 온톨로지 기술과 국제표준화기구(ISO) 중심의 토픽 맵(Topic Map) 기술이 주류를 이루고 있다.

전자는 현재의 웹에 자원(주어)·속성(술어)·속성값(목적어) 등 자원을 기술하는 언어인 메타데이터를 부여해 정보의 의미를 이해하고 처리할 수 있게 하는 기술이다. 후자는 ISO의 XML 기반 표준 기술언어인 XTM 언어를 이용해 정보와 지식의 분산 관리를 지원하는 기술로, 지식층과 정보층의 이중 구조를 띤다.

시멘틱 웹이 실현되면 컴퓨터가 자동으로 정보를 처리할 수 있어 정보시스템의 생산성과 효율성이 극대화된다. 컴퓨터 혼자 전자상거래를 할 수 있고, 기업의 시스템 통합(SI), 지능형 로봇 시스템, 의료 정보화 등 다양한 분야에 응용할 수 있다.

* 온톨로지 : 시맨틱 웹의 핵심요소는 온톨로지(Ontology)란 것으로, 사람의 마음속에 존재하는 내재적 생각이나 외재적 세계의 현상에 대하여 공유하는 개념을 컴퓨터가 이해할 수 있는 형식으로 명시적으로 정의 및 규정하는 것을 뜻한다.
 

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Semantic Web: What Is The Killer App?

Written by Alex Iskold / January 9, 2008 10:22 PM / 42 Comments

The Semantic Web has been in the making for some time and people think it is nearing maturity. We have written about this trend extensively, with our two most notable posts being an analysis of the challenges of the classic bottom-up approach and the promise of the new top-down one. Regardless of how the Semantic Web will come about, for it to flourish it needs to hit the mainstream. There is no way that consumers will appreciate the elegance and mathematical soundness of RDF and OWL. People don't care about math, they care about utility and even more, about fun. What the Semantic Web needs, then, is a killer app.

Whatever it is, it needs to layer an understanding of semantics on top of a consumer application. The consumer application needs to be so cool and so viral that people will be open to learning that it is powered by semantic technologies. In that case, it will be possible to further market applications as Semantic Web apps. Consumers will understand that if one Semantic Web application has potential, so might others. In math, this is called proof by induction. In marketing this is called creating a market. In any case, it needs to be done.

In this post, we analyze several existing and potential applications of semantic technologies and look for the killer app.

Natual Language Understanding

Since the beginning, the Semantic Web has been associated with Artificial Intelligence. The idea of representing information in structured form so that computers can "understand it" and then solve complex problems was one of the keystones of the Semantic Web vision. The problem is that representing billions of existing web documents as RDF is a rather daunting, if not impossible task. An alternative would be to "teach" computers natural language. If an application could read the page the way we read it and interpret what it says, the annotations would not be necessary.

Natural language processing has been the Holy Grail of AI for awhile now. However, it is a very difficult problem, because humans are born with the innate ability to understand language and we learn it not in a vacuum, but in the context of life. Certainly if we could replicate that with computers, it would be amazing and it would be the killer app. The problem is that this is not on the horizon. The Semantic Web technologies of today are not able to represent natural language in its entirety, and this is not really even their goal. Even if we could represent each page completely, there is still the matter of interpreting structure into semantics, which is the magic that our brain does so well and so easily.

Genie In The Bottle

Related to natural language understanding, is another idea that is not on the horizon. John Markoff called it "the perfect vacation." I call it the "Genie in the Bottle" to illustrate the impossibility of this. There is a misunderstanding about the Semantic Web which is floating around, which equates the Semantic Web with ability to solve really hard problems. It is simply not true.

For example, if you go to a new travel agency and ask them to book the perfect vacation for you, the travel agent will not be able to do it, because she does not know you. In order to find the perfect vacation there needs to be constraints: where you've been before, who you are going with, what you like to do, what is your budget, etc. Finding the "perfect" vacation is not a one shot deal, it is a process, which leverages iteration and memory.

True, with the Semantic Web the information is structured, but it does not mean that the computer can necessarily solve complex problems. These are two completely different things. Just because you have a map, does not mean that you know the best way to get from point A to point B. Having a map is necessary, but it is not sufficient, you need the algorithm to find the best path. There is a big difference between asking what is the capital of France and what is the cheapest airfair today to fly from New York to Paris. And the even harder question is: Where should I go on vacation next? Computers are not going to give us an instant, perfect answer to this question anytime soon, if ever. Again, this would be the killer app, it is just not likely to happen.

Semantic Knowledge Databases

So what is realistic and possible today? The first in the list of growing applications are Semantic Knowledge Databases. The two examples that we will look at here are Freebase and Twine. While Freebase is focusing on building essentially a semantic equivalent of Wikipedia, and Twine is focused on a personal semantic database, both are databases, both focus on knowledge management, and both are Wikipedia-like. The advantage of these databases over Wikipedia is that they represent information in a structured way and support queries. To understand the difference, take a look at the Alicia Keys page on Freebase and on Wikipedia. At first glance they are very similar, but Freebase "knows" that Alicia Keys is a blues singer and it then knows other blues singers. For Wikipedia, blues is just another page, not a music genre. So Freebase can potentially answer a question of listing all blues singers, while Wikipedia can not.

This is certainly interesting but the question is will people care? Can the end consumer tell the difference? Unlikely. Today Wikipedia contains definitive references on a vast number of topics. Like Google, it is easy to search and find relevant information, and as a result, people are not likely to be in need of a better Wikipedia. With Twine the situation might prove to be different, because personal knowledge management is an important problem. The first question is: Are their enough people who want to be efficient in managing personal knowledge? I think the answer is increasingly likely to be "yes." And the second question is: Does knowing the semantics of knowledge help you build the best application? At the very least Twine has to beat del.icio.us bookmarks and ideally needs to do for personal knowledge management what Highrise is doing for CRM.

But beyond the execution, there is still another problem. For a semantic knowledge base to be the killer app it needs to ignite imagination and capture people's hearts and minds. This is not likely to happen. We appreciate libraries, we can not live without them, but we take them for granted. Knowledge has been commoditized thanks to Google, Wikipedia, and the blogosphere, and is perceived as abundant and unexciting. For this reason Semantic Databases are not likely to be the killer apps -- but they might become a stepping stone towards one.

Semantic Search

An early candidate for the killer app in the semantic web category was search. First Hakia and more recently Powerset marketed the idea that a semantic search engine, one that is based on the understanding of natural language, can beat Google. On top of having the pressure to deliver qualitatively better results, Semantic Search companies also have to, at least approximately, solve the problem of natural language understanding, which as we discussed earlier is a very difficult one.

Where things stand right now, it does not look like search is the killer app for semantics. The understanding of natural language does not seem to give you a noticeable edge in getting better search results. At least in the comparisons that we have performed earlier there is no major difference. The statistical algorithm deployed by Google is precise and good enough, which is why it has been the clear leader in web search for the past 8 years. To unseat Google will require more than incremental improvement in search, it will likely take a paradigm shift and the creation of a different web experience. Below, we discuss how "discovery" could possibly take a bite out of the pie, but as of now Google's algorithm remains good and strong.

Social Graph

After Tim Bernes-Lee posted his thoughts on the Social Graph, a discussion began on the web in which people wondered if the Social Graph is in fact the Semantic Web. This, however, is a gross misinterpretation of the post. The Social Graph is not the Semantic Web, nor is it the killer app of the Semantic Web. They are just two separate concepts. The confusion comes from the fact that they both are Mathematical Graphs or a Network. The underlying structure of both consists of nodes connected by links. Many things in the nature and society are networks, so it is not surprising that meaning and people fall into this category.

If anything, it is more correct to say that the Social Graph is a subset of the giant, all encompasing Semantic Web. Knowing how people are connected is important in order to solve the perfect vacation problem. After all, a perfect vacation should be taken together with perfect friends, right? But jokes aside, the Social Graph is an interesting and important trend for 2008, however, it is not really related to Semantic Web.

Shortcuts

Increasingly, we are seeing a new breed of Semantic Applications, which we generalize as shortcuts. This category includes SnapShots from Snap, BlueOrganizer and SmartLinks from AdaptiveBlue, Shortcuts from Yahoo!, and In-text search from Lingospot. What is common between all these technologies is that they leverage the simple semantics of the content to deliver additional information. In the case of Snap and AdaptiveBlue, the semantics is defined by the URL, while Yahoo! and Lingospot perform text analysis.

Regardless of the method, all of these technologies deliver related information via Ajax popups. That is, they leverage semantics to pull the information from the web. This is essentially discovery or reverse search. When the user is looking at a book there is a preview with a brief description and the cover image, when the user encounters a stock symbol he is presented with a stock chart, analysis and additional links to the company, when the user is looking at a music album there is a play button, and when the user encounters a movie there is an ability to watch the trailer in place. The shortcuts remove the need to search, instead, the related content from the web comes right into the page.

Today's shortcut technologies are simple and still in their infancy, but they are among the most successful examples of semantic applications. However, we can not call them the killer app for several reasons.

First, people perceive them as advertising, which is not the point. Snap certainly made an early push into ads, but this is not a representation of what these technologies will look like in the future. Second, in their current implementation, all of these technologies are utilities. For the same reason that people are not going to get emotional about personal knowledge management, they will not be emotional about shortcuts. Shortcuts will also be taken for granted.

Yet, shortcuts hold the most promise. With a few more iterations these technologies are going to get slicker and more precise. They will leverage content and micro-context to reduce the amount of search. They will become more personalized based on user behavior. And once this happens it will be a big deal.

Full Disclosure: Alex Iskold is the founder and CEO of AdaptiveBlue.

Conclusion

We are still waiting for the killer app for Semantic Web, something that can get viral and turn semantics into a marketing term. Problems like natural language understanding still remain difficult to solve, and the solutions do not appear to be on our horizon right now. It also appears that a semantic search engine, at least based on the ones we have seen to date, does not have a substantial advantage over Google. We are seeing the rise of early Semantic Knowledge Databases, but while we expect them to get better and more interesting, they are more likely to be the stepping stones to the killer app, rather than the app itself.

In the mean time, we are seeing the rise of shortcut technologies, which leverage the basic semantics of the content, like URL and simple context analysis, to deliver relevant information, links, and media directly into the page. While still very early, these technologies hold the most promise because they are simple and useful. We expect that the next generation of these technologies in conjunction with personalization will deliver an interesting alternative to search -- contextual discovery. We will discuss this alternative in more detail in a future post.

Now tell us what you think the killer app for Semantic Web will be? Which of these technologies do you think is the most promising?

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2008 Web Predictions

Written by Richard MacManus / December 23, 2007 11:19 PM / 79 Comments

What Web applications and trends will make it big in 2008? In this post the RWW authors ruminate on the current trends in Web technology and look forward to what 2008 might bring us. Topics include Google, semantic web, online advertising, recommendation systems, Facebook, digg, open standards, Mobile Web, search engines, and much more!

So check out our predictions for '08 and please contribute your own in the comments. Also you may want to review our track record for 2007 Web predictions.

Richard MacManus, Editor, ReadWriteWeb:

1. Semantic Apps will become popular in 2008, due to their ability to get better content results and make better data connections. Think search engines like Hakia and Powerset, wikipedia-like efforts like Twine and Freebase, and apps that use semantic technologies under the hood (such as AdaptiveBlue and Snap).

2. In tandem with #1, Google will experiment more with Semantic Apps in '08. The Knols project, although not overly semantic, is a hint of this direction.

3. Web Services platforms will be a fierce battleground in '08, with Amazon, Microsoft, Google, Mozilla and others competing to provide 'Web OS' and online storage to consumers. Unfortunately this may spell the end of a number of startups in this space.

4. Zoho and/or ThinkFree will be acquired by big companies wanting to leapfrog into the Web Office space.

5. The online advertising market will consolidate, after the spate of acquisitions in 2007. CPM will continue to dominate for media brands and CPC for niche sites, although there will be experimentation in VRM and other forms of highly specific targeting of ads. Privacy issues will prevent the latter from becoming mainstream though. The much-hyped CPA (Cost per Action) will continue to be a pipe dream, because publishers simply don't want it.

6. The big Internet companies will surprise us all by embracing open standards, and attempting to compete with each other with features instead of data lock-in (OK, this could just be wishful thinking!).

7. The most interesting innovations on the Web in 2008 won't happen in Silicon Valley, but in Asia (China, Japan, Korea). At least one startup from China will break through in the US market with Twitter-like success in 2008 - and it will almost certainly be a Mobile Web app.

Marshall Kirkpatrick, Lead Writer, ReadWriteWeb:

1. Twitter will be acquired.

2. Most ad networks will start producing their own content to advertise against; and some content companies today will get acquired by ad networks.

3. Online video will become so ubiquitous, including live and mobile, that everyone will wonder how the internet existed without it. It won't feel like a big deal, though.

4. A handful of big companies will let you start logging in with an OpenID associated with your account.

5. The value of recommendation engines will become all the more clear; the era of data will be celebrated.

6. People will rebel against Google, at least a little bit. Maybe.

7. People engaged in the new web will do some really awesome stuff that we'll all be in awe of.

Josh Catone, Lead Writer, ReadWriteWeb:

1. Tumblr will be acquired.

2. Privacy will be a growing concern in the mainstream, but ultimately people won't really take any action and for the most part, things won't change. Some companies and groups (think Mozilla) will push for better privacy controls for users, while others (think Facebook) will continue to push the envelope and continue down a slippery slope. Users will eventually push back, but I am hesitant to say that proverbial "straw that breaks the camel's back" will come in 2008.

3. OpenID will be adopted by more startups and larger web companies, but most people (mainstream users) still won't use it - that's a couple of years off.

4. Facebook will continue to grow and their platform will be adopted by other large social networks. Google will sweat.

5. Mobile web usage will be a big story in 2008. It's already big in many parts of the world; and Westerners are about to get hooked. With new mobile devices that makes web surfing less painful, people will be more and more connected away from their computers.

6. Mainstream media coverage will be a catalyst for the adoption of Web Office apps by consumers; and Microsoft will eventually be forced to change their Web Office strategy and offer a fully online office suite (but that latter won't happen in 2008). Offline mode (Gears, AIR, Silverlight, etc.) will be what really tips the scales and causes mainstream users to to embrace the as-of-yet unfamiliar world of Web Office applications.

Alex Iskold, Feature Writer, ReadWriteWeb:

1. 2008 will be slow and cautious, with the first half dominated by recession or fear of recession.

2. Facebook is going to see the same kind of decline in popularity in 2008 that MySpace saw in 2007.

3. Digg is going to be acquired by one of the mainstream media conglomerates.

4. Implicit applications, which monitor our habits and automatically infer our likes, will rise.

Emre Sokullu, Feature Writer, ReadWriteWeb

1. Facebook will acquire companies that do the following, in order to strengthen their advertising unit: personalization, behavior tracking, image recognition (Riya?)

2. Facebook will release a browser.

3. However, despite all that... Facebook will decline.

4. Google OpenSocial will be a failure; Google will try to create its own social networking empire by making acquisitions in this space.

5. Microsoft will become more aggresive and buy many popular companies at once (remember Ballmer's quote). Candidates include SixApart, Technorati.

Sean Ammirati, Editor, ReadWriteTalk (our podcast show):

1. Google will really start looking vulnerable in 2008. While the 'one trick pony' comment by Steve Ballmer drew sarcastic responses, this will begin to look prophetic. While they'll maintain market share in the search industry, the lack of traction in any other of their other initiatives will start to cause frustration. Plus, they will increasingly be perceived as the 'evil' company in many of these new initiatives.

2. Closely related, Yahoo's Hack strategy (see ReadWriteTalk's podcast with Bradley Horowitz) will start to bear fruit and things will look much more optimistic in Sunnyvale this year.

3. Facebook will start to feel pressure from two trends that will emerge on the web: distributed social networks and distributed commerce systems. For distributed commerce systems, look to see a first proof of concept from the VRM project. Chris Messina's diso project with Wordpress will be a great proof of concept for distributed social neworks.

4. Non-search advertising on the web will increase in value significantly. This will be done through a lot of innovation in the ad targeting systems (both behavioral and contextual) and new metrics being adopted by Madison Ave beyond CPC and CPM.

5. There will be a lot of innovation in the hyper-local space, putting the final nail in the newspaper industry's coffin. This will include companies like Outside.in and Yelp moving toward widespread use and new web properties (from both startups and big Internet Cos) emerging.

6. Finally, a 3G iPhone! OK, I don't know if this is a prediction, but I really really want it to be true :)

Charles Knight, Editor, AltSearchEngines (RWW network blog)

1. In the 1st Q 2008, the true "Google Killer" in search will be in Stealth Mode. In 2nd Q 2008 the first prototype will begin in closed Alpha mode. In 3rd Q 2008 it will be ready for the final closed Beta testing. In 4th Q 2008 it will launch and "Rock and Shock" the world!

2. The classic Vertical Search Engines (Job Search, Health, Consumer Electronics, Shopping, Video, People, more...) will continue their dominance over all other Search Engines in their various niches.

3. The Alternative Search Engines will pick up the pace of partnerships and cooperation, for their solid mutual benefit.

4. Mainstream Media interest in the Alts will increase until it begins to rival coverage of the five major search engines.

5. The trend towards 'widgetization' of the Alts will continue. Approximately 2 in 10 Alternative Search Engines (20%) have widgets now, and that number will double in 2008 to 4 in 10 or 40%.

Conclusion

Now it's time for you to tell us your Web predictions for 2008. Please leave a comment or trackback below!

Crystal Ball image by Blue Cubic Electron Syncrony, via Flickr

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구글 흔들리고 지능형 웹 뜬다
리드라이트웹이 전망하는 2008년 웹의 변화
2007년 12월 27일 (목) 12:55:25 이정환 기자 ( black@mediatoday.co.kr)
리드라이트웹이 2008년 웹의 변화를 예측한 결과는 흥미롭다. 장황하지만 간단히 요약하고 해설을 덧붙인다 (원문 : http://www.readwriteweb.com/archives/2008_web_predictions.php).

   
  ▲ 리드라이트웹.  
 
먼저 세계 최대의 검색 서비스로 자리를 잡은 구글의 아성이 흔들릴 것이라는 전망이 많다. 구글 킬러 모델이 나타나거나 사용자들의 반발이 시작될 것이고 의욕적으로 도입한 새로운 사업 모델은 실패하거나 신뢰를 잃게 만드는 요인이 될 수도 있다. 특화된 검색엔진이 틈새 시장을 구축할 것이고 위젯 형태의 검색엔진도 활성화 될 것이다.

또한 시멘틱 웹도 인기를 끌 전망이다. Hakia나 Powerset, Twine, Freebase 같은 검색 엔진에 주목할 필요가 있다. 사용자들의 습관과 기호를 추측하고 모니터링해 최적의 검색 결과를 찾아주는 검색엔진이 나타날 것이고 데이터들 사이의 의미를 짚어내는 지능형 웹 프로그래밍이 활성화 될 것이다.

웹 오피스의 약진도 주목할 필요가 있다. 웹 오피스란 문서 편집이나 스프레드시트, 프레젠테이션 같은 소프트웨어를 별도의 응용 프로그램 설치 없이 웹에서 이용할 수 있는 서비스를 말한다. 씽크프리나 조호 같은 웹 오피스 서비스는 대형 인터넷 기업들에 인수합병될 가능성도 있다. 씽크프리는 우리나라 한글과컴퓨터에서 개발, 국내보다 해외에서 더 유명한 서비스다. 마이크로소프트 역시 웹으로 전환을 서두를 수밖에 없을 것이라는 전망도 있다.

실리콘밸리 뿐만 아니라 중국이나 일본, 한국에서 세계를 깜짝 놀라게 할 새로운 웹 서비스가 나타날 수도 있다. 중국에서 창업한 트위터 같은 서비스가 미국까지 치고 들어올 수도 있다. 인수합병도 활발해 질 것이다. 마이스페이스가 그랬듯이 페이스북도 쇠퇴할 것이라는 전망이 있는 한편, 지속적인 성장에 무게를 두는 전망도 있다. 구글 등에 인수합병 될 것이라는 전망도 있다. 마이크로소프트가 식스어파트나 테크노라티 등을 인수할 가능성도 있다. 딕닷컴 역시 인수합병 대상으로 거론되고 있다. 씽크프리나 조호 역시 매력적인 인수합병 대상이다.

한편, 데이터를 가둬두는 전통적인 웹 서비스는 도전을 받게 될 것이다. 오픈 스탠더드를 내세우면서 공격적으로 획기적인 서비스를 시도하는 새로운 사업모델이 나타날 것이다. 네이버처럼 폐쇄적인 데이터베이스를 운영하는 사이트는 딜레마에 직면하게 될 것이다.

지역에 기반한 언론이 성장할 것이다. Outside.in과 Yelp를 주목할 필요가 있다.

오픈 아이디를 도입하는 기업이 늘어나겠지만 큰 인기를 끌지는 못할 것으로 보인다. 오픈 아이디란 하나의 아이디로 여러 사이트에 동시에 로그인할 수 있는 시스템을 말한다. 한 번만 만들어 두면 새로운 사이트에 가서도 회원 가입 없이 서비스를 이용할 수 있다. 국내에서도 마이아이디 등이 오픈 아이디 서비스를 시작했지만 아직 큰 인기는 끌지 못하고 있다.

온라인 광고 역시 큰 변화를 맞게 될 전망이다. CPM(Cost per iMparession, 정액제) 방식 광고가 여전히 대세를 이루는 가운데 CPC(Cost per Click, 클릭당 과금) 방식이 틈새 시장을 뚫을 것이고 VRM(Visitor Relationship Management, 방문자 관계 관리) 방식의 실험이나 다른 형태의 타깃팅 광고 역시도 활발해 질 것이다. 다만 개인 정보보호 이슈가 걸림돌이 될 것으로 보인다.

온라인 비디오는 생방송과 모바일 등을 포함, 유비쿼터스 환경으로 옮겨갈 것이다. 언제 어디서나 인터넷에 접속해 비디오를 재생할 수 있게 된다는 이야기다. 아이폰이 선도적인 역할을 맡게 될 것이다.
최초입력 : 2007-12-27 12:55:25   최종수정 : 0000-00-00 00:00:00

이정환 기자의 다른기사 보기 

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성공을 위한 10가지 방법

 

1. Do something you believe in and love to do.

자신이 좋아하고 옳다고 믿는 일을 하라.

 

2. Be willing to start at the bottom.

쾌히 밑바닥부터 시작하라.

 

3. Look for opportunities to improve your skills.

자신의 능력을 향상시키기 위해 기회를 찾아라.

 

4. Don't let obstacles stop you.

장애물이 있다고 중단하지 말아라.

 

5. Be willing to take risks.

위험을 각오해라.

 

6. Do the footwork.

열심히 사방으로 뛰어라.

 

7. Never give less than your best.

자신이 줄 수 있는 최고의 것을 주어라.

 

8. Give credit to those who helped you along the way.

늘 도와준 사람들의 공을 잊지 말라.

 

9. Don't think you know it all.

모든 것을 다 안다고 생각하지 말아라.

 

10. There is no point in being successful if you don't enjoy life.

인생을 즐기지 않는다면 성공할 필요가 없다...

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오늘은 제가 평소에 생각해오던 CEO나 리더가 갖추어야 기본적인 자세에 대한 저의 짧은 소견을 얘기드릴까 합니다.

리더의 기본적인 자세란 표현이 다소 엉뚱하게 느껴질 수도 있겠지만, 대부분의 직장인이라면 한번쯤 생각하게 되는 "성공적인 삶에 대한 태도"를 리더란 관점에서 생각해 본 것입니다.

전 리더가 가져야 할 가장 중요한 자세(마음가짐)을 한마디로 표현하라고 한다면 아마 다음과 같이 얘기드리고 싶습니다.


" 가슴은 뜨겁고, 머리는 차갑게 "

(가슴은 화산처럼 뜨거운 마음을, 머리는 얼음처럼 차가운 냉정함을)


즉 리더는 '뜨거운 가슴'과 '냉철한 머리'가 적절하게 조화될 때, 비로소 최고의 기업과 조직을 만들 수 있다는 의미입니다. 만약 리더의 가슴과 머리가 모두 뜨거워버리면 리더가 자기자신을 통제하지 못하므로 감정에 치우친 의사결정과 판단을 할 가능성이 높게 되고, 가슴과 머리가 모두 차가우면 다른사람으로부터 진정한 리더십을 이끌어낼 수 없기 때문입니다.
 
그럼 이 내용을 하나씩 생각해보면,


1. 가슴은 뜨겁게


"가슴은 뜨겁게"란 다음과 같은 의미를 포함하고 있습니다.

(1) 가슴이 뜨거운 사람 : 사업을 꼭 성공시키고 말겠다는 그 누구보다 강한 열정과 지칠줄 모르는 Energy를 갖고 있는 사람 --> PASSION(열정)

(2) 가슴이 따뜻한 사람 : 사업의 세계가 비록 냉정하고 치열한 전투의 연속이지만, 비즈니스에 있어서나 인간관계에 있어서 가장 기본적인 상도를 지킬 줄 아는 사람 --> 배려

이러한 자세는 아래에서 설명될 "차가운 머리" 5가지 요소의 기본적 토대가 되어야만 합니다. 그래야만 그 5가지 요소가 비로소 힘을 가질 수 있기 때문입니다.


2. 머리는 차갑게

5가지 요소 : 자기통제 + 엄격 + 강함 + 투지 + 승부심

(1) 자기통제 => 스스로의 감정을 통제하는데 있어 가져야 할 자세

(2) 엄격 => 작은것~큰것까지의 다양한 의사결정을 하는데 있어 가져야 할 자세

(3) 강함 => 조직관리 및 리딩을 위해 가져야 할 자세

(4) 투지 => 얼음같이 차가운 냉정함을 통해 경쟁상황을 계속 지배하는 자세

(5) 승부심 => 어떤 상대가 오더라도 이기고자 하는 냉철한 투지속에서 승부심을 발휘하는 자세



(1) 자기통제 = 외부자극에 대해 자신의 반응을 통제할 수 있는 능력

사업을 하다보면 여러가지 일을 경험하게 됩니다. 외부 제휴업체를 만나거나, 아니면 내부직원들과의 미팅에서 자신의 기준에는 벗어난 의외의 경험을 하게됩니다. 하지만 이들 경험에 대해서 일일이 감정적 대응을 하게되면 자신의 중심을 놓치기 쉽습니다. 즉 감정적 통제를 하지 못하고 불필요하거나 과다한 방법으로 표현됨으로써 사업에 방해가 되는 결과를 초래할 수 있기 때문입니다. 이를 위해선 다양한 외부자극이나 상황변화, 외부위협 등에 대해서 즉각적인 감정적 반응을 하는 것이 아니라, 현재 어떻게 반응하는 것이 보다 현명한지를 충분히 생각하고 자신의 반응을 선택해서 반응할 수 있어야 합니다. 이렇게 된다면 감정적 판