你屬於我所熱愛的那個世界

摘自『論我所熱愛的那個世界』

《百年孤獨》的作者，我們熟悉的大作家加西亞‧馬爾克斯(或譯馬奎斯)名滿天下之後聽到各種贊辭，但只有1981年法國總統密特朗說的一句話使他最為感動，以至使他禁不住熱淚盈眶。這句話就是：「你屬於我所熱愛的那個世界。」這是密特朗在愛麗舍宮頒發給馬爾克斯榮譽騎士勳章時說的，我一直記在心裡。每次想起這句話，我心中便會湧起不可抑制的情感。

我所熱愛的那個世界是什麼?它在哪裡?它是一個國度還是一個部落?它是黃花地還是百草園?它在此岸還是在彼岸?我既說不清也無法命名。也許老子的「名可名，非常名」，在此倒可為我辯解。你發現我在打破地理意義上的「鄉愁」模式之後仿佛又產生另一種鄉愁，另一種眷戀，這是真的。我的眷戀就是對於「我所熱愛的那個世界」的眷戀，我的鄉愁也正是對於「我所熱愛的那個世界」的沉思、憧憬與嚮往。

我們一生中，有多少次，可以無憾、無畏、無懼、無悔的對一個人說：「你屬於我所熱愛的那個世界。」

相關連結:

• 漂流手記第六卷 ：「父女兩地書─共悟人間」
• 上海的版本
• 再復迷網站

大學的理想和性格

這學期修了一門和大學教育有關的課，需要交兩份和高等教育有關的報告，所以從書裡和網路上找了一些資料，將大學的源流和理念的遞嬗，作個簡短的筆記。資料主要參考自金耀基先生的『大學的理念』，以及某些大陸的網站。交出去的報告，說穿了，只是資料的整理（說難聽點，就是剪貼啦），沒有任何有意義的「意見」。不過大學理念的嬗變，值得記下來作為參考。

以下是報告中大學起源和理念闡述部份的節錄：

大學自其出現始，就因為其在文化傳承和社會進步上的特別作用而有別於其它機構。特別是一些經歷近千年風雨仍巍然自立的大學，因為其獨特的風格和對人類的貢獻而閃爍光芒。所以，大學是有精神的，唯其精神，使之能經世而獨立，歷久而彌新。在近代以來的大學發展史上，我們總是可以看見一些光輝的名字，如 Newman、FIexner、Von Humboldt、蔡元培、梅貽琦、Kerr等，大學功能的發展也從單純的「傳道授業解惑」到「以研究為重」再到今日的「教研並重並須服務於社會」，而 Kerr 更是用 Multiversity 來形容今天的大學，以表明今日大學功能之復雜、目的之多元。

大學的起源可以溯到中國的先秦，西方的希臘與羅馬。《大戴禮‧保傳》中寫道，「束髮而就大學，學大藝焉，履大節焉。」據此，大學應當是學大藝、履人大節的地方。漢代的人學、隋朝的國子監都是中國古代意義上的大學。中國古代四書之一《大學》的開篇之語，「大學之道，在明明德，在親民。在止於至善」，則可說是從某個方面體現了中國古代大學的精神和理念。但現代大學之直接源頭則是歐洲中古世紀的大學。大學是中古的特殊產物，中古是宗教當陽稱尊的世紀，他對西方文化的影響向來是學術上纏訟不休的事，但沒有人否認大學是中古給後世最可稱美的文化遺產。

大學的理想和性格幾個世紀來以發生許多的變化。第一本給大學系統性地刻畫一個明確的圖像的重要專著也許是十九世紀（一八五二）的牛津學者紐曼 (John H. Cardinal Newman ) 的「大學的理念」( The Idea of a University )。紐曼認為大學是一個提供博雅教育 ( liberal education ) ，培育紳士的地方。簡言之，紐曼之大學理想著重在對古典文化傳統之保持，教育之目的則在對一種特殊型態之人的「性格之模鑄」 (character formation ) 。紐曼的大學之理念顯然是「教學的機構」，是培育「人才」的機構。

洪博德（Karl Wilhelm von Humboldt,1767-1835）是19 世紀德國著名的教育家，由他倡導創辦的柏林大學，追求教學和科學研究相統一，使得科學研究職能在大學中得以確立。洪博德強烈主張，大學不僅僅是一個教育機構，大學更應是一個研究中心。一改過去歐洲中世紀大學僅是保存和傳授知識的傳統，認為大學應重在發展知識而不在傳授知識，大學應是知識創新的源泉。

德國大學的新理念，在美國大學的先驅者佛蘭斯納 ( A. Flexner )成書於一九三０年的「大學」( Universities ) 一書中獲得系統性的闡揚。他特別強調「現代大學」，以別於早他七十幾年的紐曼之「大學」。佛蘭斯納肯定「研究」對大學之重要，肯定「發展」知識是大學重大功能之一，但他卻給「教學」以同樣重要的地位。他指出：「成功的研究中心都不能代替大學」；也即大學之目的不只在創發知識，也在培育人才。

自二次大戰之後，大學教育在世界各地都有蓬勃的發展。而在美國尤其獲得快速與驚人的成長。在一八七六年前，美國只有書院 ( college )，還談不上有真正的大學，而此後在吉爾曼 ( Gilman ) 與愛略特 ( C. Eliot ) 等人的改革發展下，步德國大學的後塵，才一步步提高大學的水準。美國的先進大學，一方面承續德國大學重研究之傳統，一方面也承繼英國大學重教學之傳統。美國的大學狂熱地求新，求適應社會之變，求趕上時代，大學已徹底地參與到社會中去。由於知識的爆炸及社會各業發展對知識之依賴與需要，大學已成為「知識工業」( knowledge industry ) 之重地。

20世紀中期以後，大學理念和精神最主要的變化就是現實的貼近和現實感的增強。由於知識經濟社會知識對社會、經濟的促進作用，大學已成為知識工業的重地，知識與經濟的結合，使得大學已自覺不自覺地成為社會的「服務站」。20世紀90年代，聯合國教科文組織（UNESCO）在《促進高等教育的變革與發展的政策性文件》中提出建立「前瞻性大學」的問題。前瞻性大學的理念要求大學不僅不能作為與世隔絕的象牙塔，也不能單純傳授知識、發展知識，而應該成為地區、國家乃至全球問題的自覺參與者和積極組織者，從而服務於社會。

... omitted ...

On Blogosphere Size

I asked a question in my April 23's post The biggest social network you'll never see that who have done the estimation of blogosphere size. It seems that I asked a stupid question. Technorati regularly publishes the "State of Blogoshpere" report on a quarterly basis. The latest report, The State of the Live Web, was published on April 5,2007. As stated in the report, there're 70 millions blogs tracked by Technorati ( I wrongly stated there're nearly 60 millions out there in previous post ).

OK, let's on to the numbers. The pictures paints more that a thousand words. The charts below tell us the story. Technorati is now tracking over 70 million weblogs, and we're seeing about 120,000 new weblogs being created worldwide each day. That's about 1.4 blogs created every second of every day.

Though, a total of 70 million blogs have been set up. But the data from Technorati show that only 15.5 million bloggers updated their sites during the last three months, up slightly from 15.3 million in October (2006).

The summary of the report are as follows ( the words in red are added by me) :

• 70 million weblogs
• About 120,000 new weblogs each day, or...
• 1.4 new blogs every second
• 3000-7000 new splogs (fake, or spam blogs) created every day
• Peak of 11,000 splogs per day last December
• 1.5 million posts per day, or...
• 17 posts per second
• Growing from 35 to 75 million blogs took 320 days
• 22 blogs among the top 100 blogs among the top 100 sources linked to in Q4 2006 - up from 12 in the prior quarter
• Japanese the #1 blogging language at 37% ( I must admit that I have totally no idea about this )
• English second at 33%
• Chinese third at 8% ( Traditional and Simplified Chinese Blogs combined ?? )
• Italian fourth at 3%
• Farsi a newcomer in the top 10 at 1%
• English the most even in postings around-the-clock
• Tracking 230 million posts with tags or categories
• 35% of all February 2007 posts used tags
• 2.5 million blogs posted at least one tagged post in February

(All of the materials presented here are licensed under a creative commons for-attribution license. As long as the Technorati logo and links are kept intact. Refer to the report for copyright notice.)

Read also :

• The biggest social network you'll never see
• Mapping the blogoshpere
• Big Shots of Blogdom
  

[Info] - Workshop on Data Mining in Web 2.0 Environments

Workshop on Data Mining in Web 2.0 Environments will be held conjunction with ICDM 2007(International Conference on Data Mining) on October 28, Omaha, United States. Topics of interests are:

• analysis of blogs
• tag clustering and visualization
• synonym and homonym resolution in tags
• visual and textual information extraction
• temporal analysis
• data streams, trend detection, and concept drift
• application of web and text mining to wiki content
• discovering social structures and communities
• evolution of online social networks
• predicting user behavior
• analysis of dynamic networks
• discovering misuse and fraud
• combining the web with data from other sources, mining with mashups
• deriving profiles from usage
• personalized delivery of information
• applications, case studies

This year's International Conference on Weblogs and Social Media is over. Next year, the conference will be held in Chicago. There's one thing noteworthy that the news, videos, tutorials, and papers are presented in the blog of the conference. Yes, we're doing what we're saying, watching and studying.

Awareness Watch™ Newsletter is a free monthly publication that highlights the latest resources and sites on the Internet pertaining to current awareness happenings, new and reviewed sources for research and search, knowledge discovery, data mining and related updates and alerts. The May issues of the newsletter are out.

（看來，這個部落格變成我的 Data Mining 書籤了，或許我該試試 del.icio.us ? )

五年級雜草

我的朋友金剛，是一個很精彩的人。他的精彩，不僅在於經歷多采多姿，他曾是廣告片的副導，做過網路公司的行銷經理（那時我們是一起共事的戰友），也是只為金字塔頂端階層服務的腳底按摩師，客串過廣播節目的配音人員，業餘的影評人，也是花店和旅行社的行銷經理，目前是加拿大航空的行銷經理。更重要的，他有一顆柔軟的心，幽默而感性的文筆，高明的攝影技巧，還有比我稍微「壯碩」一點點的身軀。

Message-Massage 是他的個人網站，裡面有他的文章、影評和攝影作品。每回看他的文章，總是混合著羨慕、會心和淡淡的惆悵，他看似幽默其實深沈的文字，把我們的共同回憶用一種不溫不火的調子緩緩道來，看了又驚、又喜又有點鼻酸。

五年級雜草（Good Old Days）是網站裡的一個單元，這個單元是屬於五年級世代的共同回憶，個人私心以為，這裡的文章比起許多講「五年級」或其後的跟風文章，要誠懇的多，也更符合我的個人經驗與回憶。標題是「五年級雜草」的文章裡，有這麼一段話：

我非常喜歡李安導演在「十年一覺電影夢」一書中所寫的：「人情是流動的，事過境遷，人事全非，它就會隨風而逝…我們現在做的話，後人還能看到一點東西；但如果我們不做，下一代無從知曉，這份情愫可能就此消逝於風聲塵埃之中！」

　或許是傳承的目的，或許是為尋找自己存在的證據，或許不願意美好記憶消逝於風聲塵埃之中，因此，我決定寫下年輕歲月，雜草的懷舊沒有菁英來的壯烈，但是如果不做，五年級的風貌就只能存於學運。

我的奮力一「博」，受這段文字的影響很深。最近他的文章更新速度變慢了，希望金剛能夠記得這個承諾，加把勁，讓我們的共同記憶，不要淹沒在風聲塵埃之中。

金剛，很高興認識你，一起加油吧。

Birth of Data Mining

Data Mining is the evolution of a filed with long history, the term "data mining" emerged in late '80s and the researches of data mining flourished since 1990s. Many believed that the birth of data mining (or knowledge discovery) should trace back to the 1989 IJCAI workshop on Knowledge Discovery in Databases took pace in Detroit, Michigan, USA. The report was published in AI magazine and the bibex can be found at ACM digital library. The context of the document can be found at KDnuggets. (The Proceedings of the conference may be of interest).

The summary of the report are as follows:

The workshop confirmed that knowledge discovery in databases is an idea whose time has come. Some of the important research issues addressed in the workshop were:

• Domain knowledge. It should be used to reduce search space, but used carefully so as not to prevent un-anticipated discoveries. While a specialized learning algorithm will outperform a general method, a desirable compromise is to develop a framework for augmenting the general method with the specific domain knowledge.
• Dealing with Uncertainty. Databases typically have missing, incomplete or incorrect data items. Thus any discovery algorithm must deal with noise. Rules discovered in noisy data will necessarily be approximate.
• Efficiency. Exponential and even high-order polynomial algorithms will not scale for dealing with large volumes of data. Efficient linear or sublinear (using sampling) algorithms are needed.
• Incremental Approaches. Incremental algorithms are desirable for dealing with with changing data. An incremental discovery system that can re-use its discoveries may be able to boot-strap itself.
• Interactive Systems. Perhaps the best practical chance for discovery comes from systems, where a ``knowledge analyst'' uses a set of intelligent, visual and perceptual tools for data analysis. Such tools would go far beyond the existing statistical tools and significantly enhance the human capabilities for data analysis. What tool features are necessary to support effective interaction? Algorithms need to be re-examined from this point of view (e.g. a neural network may need to generate explanations from its weights).

The incremental, interactive discovery methods may transform the static databases of today into evolving information systems of tomorrow. Caution is required for discovery on demographic databases, to avoid findings that are illegal or unethical. Some of the research issues that were little addressed in this workshop, but are likely to become more important in the future are:

• Discovery Tools. Deductive and object-oriented database systems can provide some of the needed support for induction on large volumes of data. Parallel hardware may be effectively used. What additional operations should be provided by the tools to support discovery?
• Complex Data. Dealing with more complex (not just relational) data, including text, geographic information, CAD/CAM, and visual images.
• Better Presentation. The discovered knowledge can be represented not only as rules, but as text, graphics, animation, audio patterns, etc.. Research on visualization and perceptual presentation is very relevant here.

Remarks:
IJCAI stands for International Joint Conferences on Artificial Intelligence.

The Ten Commandments

I found the "commandments" in the MyShare recommendation list. The rules appeared in a well-known Taiwanese blogg [終極邊疆 BLOG] in '03. I think it's really important to bloggers, fresh and veteran. Don't forget why you're blogging and blog for yourself.

1. blogging for fun ,for yourself, at least at beginning

2. don’t force yourself to blog just for periodically update.

3. don’t limit your blog to min. or max. length.

4. don’t blog just for audience.

5. don’t be afraid of opposite comments.

6. Blogging is to share your thought, your opinion, not your ” me too”.

7. Blogging tools and interfaces are for convenience, not for “Wow! so fascinating!” The same as
your site layout.

8. If you don’t want someone reading your blog, never put it on.(Even he/she don’t know you have a blog)

9. Try to remember why you are blogging.

10. forget the first 9 rules. use the 10th instead: BLOG FOR YOURSELF!