蔣以仁. Search Problem 2 Monika Henzinger, Search Technologies for the Internet Science, Vol. 317. no. 5837, 468 – 471, 27 July 2007 Search Query: Jaguar

蔣以仁

Search Problem

2

Monika Henzinger, Search Technologies for the Internet Science, Vol. 317. no. 5837, 468 – 471, 27 July 2007

Search Query: Jaguar Jaguar(Animal) Jaguar(Automobile) Jaguar(Watch) Jaguar(OS)

檔案的目的在為未來創造知識 …records are recognized as agency assets

used to underpin current business and legal needs, as well as the basis for a knowledge management system to meet future goals. –

HOWARD P. LOWELL

DirectorModern Records

ProgramsNARA

資料探勘資料探勘走向決策支援走向決策支援彙整同一性質資料資料探勘以產生關聯相依規律視覺化顯示協助專家研判主題定義處理指引方便建立決策支援

KDD Process

DataWarehouse

Knowledge

Selection

Preprocessing

Target Data

Preprocessed Data

PatternTransformed

Data

Data Mining

Transformation

Interpretation/Evaluation

8

BI 結構Monitor

&Integrator

Complete DataWarehouse

ExtractTransformLoadRefresh

metadata OLAPServer

1. Comprehensive Performance Management2. Analysis3. Query4. Reports5. Data mining

Data Sources

Tools

Server

Data Marts

Operational DBs

Other sources

Business Intelligence

9

Gaining market intelligence from news feeds

Sreekumar Sukumaran and Ashish Sureka

SignalDr. Bhandari said, “I first noticed this when

the New York Times did an analysis after the fact showing that early indications of the Ford-Explorer-Firestone-tire problem went undetected in a federal database. Recently, a similar analysis by CNN showed that early indications of security problems at Logan, Dulles, and Newark airports, went undetected in a federal database well before the September 11 tragedy. It is clear that the cost of missing these patterns is too high to be ignored.”

資訊整合

Call Taker: James Date: Aug. 30, 2002Duration: 10 min.CustomerID: ADC00123

Q: cust sys has stopped working.A: checked cust bios and it need updated. …

Unstructured Data

Structured Data[Call Taker] James [Date] 2002/08/30[Duration] 10 min.[CustomerID] ADC00123

[Noun] Customer[Software] BIOS[Subj...Verb] customer system..stop[SW..Problem] BIOS..need

Original Data Meta Data

LinguisticAnalysis

TaggingDependency AnalysisNamed Entity ExtractionIntention Analysis

CategoryDictionary

SynonymDictionary

Category Item Visualization & Interactive Mining

Mining

IBM TAKMI(Nasukawa, Nagano,1999)

Mining target: individual text Mining unit: >texts >category labeled items extracted from text using NLP

醫學文獻告訴我什麼醫學文獻來源： Medline可發現疾病、症狀與藥物或化合物的因果關聯

1. Swanson DR. Searching natural language text by computer. Machine indexing and text searching offer an approach to the basic problems of library automation. Science. 132:1099–1104, 21 Oct. 1960.

2. Swanson DR. Fish oil, Raynaud's syndrome, and undiscovered public knowledge. Perspect Biol Med. 30(1):7–18, 1986.

3. Swanson, D.R., Complementary structures in disjoint science literatures. In A. Bookstein, et al (Eds.), SIGIR91: Proceedings of the Fourteenth Annual International ACM/SIGIR Conference on Research and Development in Information Retrieval Chicago, Oct 13-16, 280-289, 1991.

偏頭痛 ?Stress is associated with migraines Stress can lead to loss of magnesium Calcium channel blockers prevent some

migraines Magnesium is a natural calcium channel blocker Spreading cortical depression (SCD) is implicated

in some migraines High levels of magnesium inhibit SCD Migraine patients have high platelet

aggregability Magnesium can suppress platelet aggregability

Smalheiser, N.R. & Swanson, D.R.. Assessing a gap in the biomedical literature: Magnesium deficiency and neurologic disease. Neuroscience Research Communications, 15, 1-9, 1994.

文獻實証

migraine magnesium

stress

CCB

PA

SCD

All NutritionResearch

All MigraineResearch

找出新線索Fish oils雷諾氏現象

Raynauds

vasoconstrictions血管收縮

platelet aggregation血小板活化凝集

blood viscosity粘滯血症

Intermediate conceptsSwanson, D.R. (1994). Fish oil, Raynaud's syndrome, and undiscovered public knowledge. Perspect Biol Med. Autumn;30(1):7-18, 1986 .

Hypothesis generation

不得不提到的技術 - 自然語言處理 NLP

始於 1948 年倫敦 Birkbeck College 字典查詢系統

1949- Warren Weaver 之 American Interest 破解密碼

1950- 機器翻譯 (German to English, Russian to English)

1966~ 雷聲大雨點小機器翻譯字對字 (Dr. Eye?)NLP brought the first hostility of research

funding agencies.NLP gave AI a bad name before AI had a name.

資訊巨幅成長2006 年數位資訊量已達 1,610 億 GB( 相當於 161 Exabytes) 。 IDC 預估從 2006 至 2010 年間，資訊成長量約為六倍。 2010 年時，有近 70% 的數位世界的資訊是由個人使用者所創造，而至少有 85% 的資訊量是組織企業必須負起資訊安全、隱私、可靠性及相關法規遵從的責任。

The Expanding Digital Universe, http://www.emc.com/leadership/digital-universe/expanding-digital-universe.htm

0

10

20

30

40

50

60

70

80

90

100

資料量市場化價值

非結構資料

結構化資料

網路訊息新聞報導專利電子郵件文件… Oracle

Search Engine Roadmap

Full Text SearchIncluding complex

Boolean search

Exploratory Search

Wikis

Forum/Blogger

Dictionary/Ontology

Taxonomy Search

Synonym/Anatomy

Clustering/Categorize

Customized meta-search

Crawler

Personal taggingSharing

Custom Search

Integrate other search engines

Collaborative Filting

Feature Ranking

Web Page Features Extraction

(semi- and un-structure)

Feature Mapping

Filtering

Summarization(mobile)

Taxonomy search

Document Abstraction

Multiple abstractsorganization

Natural language processing/understanding

Knowledge collaborativesearch

Visualization

Ajax

Visual Technology

Affiliation (Topic Relevance

Analysis)Search log recorder

Topological Graphics

Web 2.0 or upperRecommendation

網路搜尋引擎以離線方式抓去網頁，透過建立一種內部資料儲

存方式，稱之為 (反轉； inverted) 索引，儲存資料

線上檢索

Monika Henzinger, Search Technologies for the InternetScience, Vol. 317. no. 5837, 468 – 471, 27 July 2007

Search Engine Problems

Index ComprehensivenessRelevance

Deterministic SearchSearch Query

Jaguar(Animal)Jaguar(Automobile)Jaguar(Watch)Jaguar(OS)

Problem: Scalable

J, Beall, The Weaknesses of Full-Text Searching. The Journal of Academic Librianship, 34(5):438-444, 2008.

搜尋引擎之演進第一代– 只使用“網頁內”文字資料

字頻 , 語言

第二代 -- 使用非頁內 , 網路上特殊屬性資料連接分析點擊資料 (What results people click on) 下錨文字 (Hyperlinks, How people refer to this page)

第三代– 回答 “查詢所知” 語意分析 -- what is this about? 專注使用者所需 , 非僅僅查詢關鍵資料之推定輔助使用者整合搜尋及文件分析

1995-1997 AV, Excite, Lycos, etc

From 1998. Made

popular by Google but everyone now

Still experimental

網路搜尋問題問題

查詢過於簡短不夠精確同意與相似字詞讓查詢匹配度難預期網頁作者混淆式安排 , 讓搜尋結果差強人意使用者需要額外功能 , 如過濾器

解決增加理解結果排列Trailblazer

Car Basketball team

Monika Henzinger, Search Technologies for the Internet Science, Vol. 317. no. 5837, 468 – 471, 27 July 2007

Expand

Crawler

Crawler

Basic Crawler

Hertrix

Wrapper/Clipper

HTML ParserStructural Features

Extraction

Semantic Crawler

Feature Mapping

Unstructured Document Features Extractions

(NLP)

Clipper Windows Specify

Machine Learning Approach

P2P Knowledge SharingCrawler

Filtering

Specific Feature Parse

Ontology

……

…

XML Parser

XHTML, DHTML Parser

Ontological Organization

Scheduling

Feature Transformation

Crawler ClassesAnnotated Crawler

CrawlerCrawler

Craw with specific terms/phasesCraw with specific terms/phases

Outside Search Outside Search EngineEngine WebWeb

Data SourcesData SourcesFilterFilter

Supporting Information Supporting Information from original sources &from original sources &Reference contentsReference contents

Relevant Relevant Information Information

Feed into Reference ListFeed into Reference List

AuthoringAuthoringUser processUser process

Filtering NEFiltering NErecordsrecords

LearnerLearner

Crawler ClassesPage/Section/Block/Item Specify

CrawlerCrawler

RepositoryRepository

Feature ExtractorFeature Extractor

SchedulerScheduler

LogLog

ComparatorComparatorCompare the extracted structure Compare the extracted structure

between two stagesbetween two stages

AdaptorAdaptor

Notify for manually tuneNotify for manually tune

Named Entities RecognitionNamed Entities Recognition

GUI Specification SystemGUI Specification System

LoggerLogger

時序性資訊彙整

事件分析

分群檢索

1. Walter Warnick, Problems of Searching in Web Databases. Science . Vol. 316. no. 5829, 1284, June 2007.

2. I-Jen Chiang, Discover the Semantic Topology in High-Dimensional Data, Expert Systems with Applications, 33 (1), September, 2007.

技術架構略圖

Raw text

Term similarity

Doc similarity

Vector centroid

分群

d

分類 / 文件追蹤META-DATA/ANNOTATION

d d d

d

d d d

d d

d d

d

d

d

t t

t t

t t t t t

t

t t

Stemming & Stop words

Tokenized text

Term Weighting

w11 w12… w1n

w21 w22… w2n

… …wm1 wm2… wmn

t1 t2 … tn d1

d2 … dm

Sentenceselection

摘要

Salton’s Vector Space Model一袋子字 (Bag of Words)Cosine Similarity

Jaccard index θ

Jaccard similarity coefficient

Tanimoto coefficient

A

B

G. Salton, A. Wong, and C. S. Yang, "A Vector Space Model for Automatic Indexing," Communications of the ACM, vol. 18, nr. 11, 613–620, 1975.

Curse of Dimensions

1

句意不清 : I saw the man on the hill with telescope

Using a telescope, I saw a man who was on a hill.

I saw the man on the hill with telescope

I saw a man who was on a hill and who had a telescope.


I saw a man who was on the hill that has a telescope on it.


自然語言處理新方向

1. M. Marcus. New trends in natural language processing: Statistical natural language processing. PNAS. 92. 10052-10059, 1995.

2. Current Trends in Biomedical Natural Language Processing, Ohio State University, June 20083. Tanveer Siddiqui. National Language Processing and Information Retrieval. Oxford Univ Press, 2008.4. Yorick Wilks. Natural Language Processing as a Foundation of the Semantic Web. Foundations and

Trends® in Web Science, 1(3-4). 199-327, 2009.

Text

SpeechRecognition Extractor

Speech Entities

NE

Models

地點人物

組織

The delegation, which included the commander of the U.N. troops in Bosnia, Lt. Gen. Sir Michael Rose, went to the Serb stronghold of Pale, near Sarajevo, for talks with Bosnian Serb leader Radovan Karadzic.

TrainingProgram

trainingsentences answers


Text

SpeechRecognition Extractor

Speech Entities

NE

Models


TrainingProgram

trainingsentences answers

The delegation, which included the commander of the U.N. troops in Bosnia, Lt. Gen. Sir Michael Rose, went to the Serb stronghold of Pale, near Sarajevo, for talks with Bosnian Serb leader Radovan Karadzic.•Prior to 1997 - no learning approach competitive with

hand-built rule systems •Since 1997 - Statistical approaches (BBN (Bikel et al. 1997), NYU, MITRE, CMU/JustSystems) achieve state-of-the-art performance

I-Jen Chiang

知識地圖

事件追蹤

資訊檢索

知識概念

議題內事件發生的相依關聯議題內事件發生的相依關聯

查詢以瞭解議題內相關論點

論點角度 ( 依機關、案由等 )

議題內某事件所受之影響

議題內某事件之影響

依時間追蹤事件處理狀況

深入細節以瞭解現象、處置深入細節以瞭解現象、處置

權衡輕重以瞭解處事準則權衡輕重以瞭解處事準則

事件追蹤分析議題主軸變化事件追蹤分析議題主軸變化

組合屋議題下

政府震災地區災民住宅重建信用保證基金一千億讓災民取得貸款

組合屋議題下

重建條例訂定含括工程、獎助金

Integrated BI Systems

Complete DataWarehouse

ETL

Structural Data

DBMS File System XML EA Legacy

Unstructured Data

CMSScanned

Documents Email

ETL

Text tagger & Annotator

Intermedia Data

RDBMS XML


標註

On November 16, 2005, IBM announced it had acquired Collation, a privately held company based in Redwood City, California for undisclosed amount.

DateAcquiring

OrganizationAcquisition

EventAcquired

Organization

Place Amount

Text Annotator

Date Organization Place Amount

Nov. 16 IBM Redwood City, CA

Undisclosed

Output toRDBMS

XMLoutput

On <Date>November 16, 2005</Date>, <ACQUIRING ORG>IBM</ACQUIRING ORG> announced it had <ACQUISITION EVENT>acquired</ACQUISITION EVENT> <ACQUIRED ORG>Collation</ACQUIRED ORG>, a privately held company based in <PLACE>Redwood City, California</PLACE> for <AMOUNT>undisclosed</AMOUNT> amount.

McIlraith, S.A., Son, T.C., Zeng, H.: Semantic web services. IEEE Intelligent Systems 16, 46–53, 2001

整合式 BI 系統Complete Data

Warehouse

ETL

Structural Data

DBMS File System XML EA Legacy

Unstructured Data

CMSScanned

Documents Email

ETL

Text tagger & Annotator

Intermedia Data

RDBMS XML


Knowledge-based Persistent ArchivesIngest Manage Access

(Topic Maps / Model-based Access)

(Data Handling System - Storage Resource Broker)

MC

AT

/HD

FX

ML

DT

DX

TM

DT

D

GR

IDS

EM

CA

T /

MIX

Rul

es -

KQ

L

Attribute- based Query

Feature-basedQuery

Knowledge orTopic-Based

Query

InformationAttributesSemantics

Knowledge

RelationshipsBetweenConcepts

Data FieldsContainers

Folders

InformationRepository

KnowledgeRepository for

Rules

Storage(Replicas,

Persistent IDs)

Ingest Manage Access

(Topic Maps / Model-based Access)

(Data Handling System - Storage Resource Broker)

MC

AT

/HD

FX

ML

DT

DX

TM

DT

D

GR

IDS

EM

CA

T /

MIX

Rul

es -

KQ

L

Attribute- based Query

Feature-basedQuery

Knowledge orTopic-Based

Query

InformationAttributesSemantics

Knowledge

RelationshipsBetweenConcepts

Data FieldsContainers

Folders

InformationRepository

KnowledgeRepository for

Rules

Storage(Replicas,

Persistent IDs)

NASA iLoC SBA Workspace

Ele

ctric

al

Po

we

r A

na

lysi

s

IDT DB

TopSCAPEDisciplineOntology Models

NExIOM Ontology Models

SI

T2

SI

SI

T1

RFx DB

WS

WS

WS

WS

Mapping Mapping Mapping Mapping

Translation Models

ILALBL

ILALBL

SI

W S

Semantic ApplicationInteraction LogicApplication LogicSemantic Interface C

ost

Mo

de

ling

COVE

W S

Ontology Authoring

Pe

rfo

rma

nce

M

od

elin

g

Ris

k M

od

elin

g

Tra

de

-Off

s A

na

lysi

s

Str

uct

ure

an

d

Co

nn

ect

ivity

Ele

ctric

al

Po

we

r A

na

lysi

s

W S W S W S W S W S

Text Mining for Hypertext Creation

...

Subtopic 1

A general topic

Subtopic i Subtopic M

Concept map

Hypertext

Doc 1 Doc 2 Doc N

Type of Links

...

Subtopic 1

A general topic

Subtopic i Subtopic M

Doc Doc Links

Doc 1 Doc 2 Doc N

Term Term Links DocTerm Links

TermDoc Links

Example from an Enterprise Architecture Process Ontology

Task

Goal

Role Measure

Agent

Process

fea: Mission

fea: intentOf

fea: Agency

brm: provides

brm: SubFunction

fea: hasIntent

brm: hasProcessbrm: Process

brm: usesResource

brm: Resource

brm: hasPerformance

prm: PerformanceMeasure

prm:hasIndicator

prm: GenericMeasurementIndicator

fea: Customer

prm:hasSpecialization

prm: OperationalizedMeasurementIndicato

r

brm: hasCustomer

srm: Service

brm: realizedWith

病歷紀錄整合 ROYAL MARSDEN NHS TRUST - PATIENT CASE NOTE

######:MRS ##### #######

15 Dec 1993 General Surgical

I reviewed this patient in clinic today. She has been followed

up for a left breast carcinoma for which she was treated with a

mastectomy. She had a prosthesis removed last year and has had

some improvement in the symptoms of chest wall discomfort since

then although she still gets quite sharp pains intermittently.

She has been reviewed in the pain clinic local to where she

lives but has not had much relief of her symptoms. She feels

though that she can bear with these and does not want any

further intervention at present.

On examination today there is no sign of recurrence of her

disease. Chest and abdominal examination were unremarkable. We

will see her again in a year's time.

28/03/2003, 10:35:26

ROYAL MARSDEN NHS TRUST - PATIENT CASE NOTE

######:MRS ##### #######

27 Aug 1998 Seen in the Follow Up Staging Clinic

This 65 year old lady has been reviewed in the Breast staging clinic.

As you know, she was originally diagnosed with a carcinoma of the left

breast in 1974 and treated with a total mastectomy. This was followed

with MEFUP chemotherapy. In 1982 she noticed a lump in the

infraclavicular region which was excised and this was followed by

radiotherapy. In 1994 she developed a tumour in the chest cavity that

was diagnosed with a CT guided biopsy and this was treated with VAC

chemotherapy and radiotherapy to the mediastinum. Since 1994 she had

noticed a slight deterioration and earlier this year she had problems

with occasional episodes of vomiting, nausea and general lethargy. She

was found to have lymphadenopathy in the right supraclavicular fossa

and was treated with Arimidex. Since being on Arimidex there was

originally stablisation of her disease but recently it appears that the

node has started to enlarge.

On examination today, she has a 1.5x1cm lymph node in the right

supraclavicular fossa and an essence of thickening probably due to

previous therapy in the left supraclavicular fossa. She also has

radiation changes in the lung which produced some physical sign at both

bases and there was no evidence of abdominal organomegaly.

Her recent staging investigations show that she has C5 carcinoma cells

present in the lymph node fine needle aspirate. A right mammogram is

unremarkable. An ultrasound of the liver was normal and a chest x-ray

showed some soft tissue thickening present in the left axilla due to

previous therapy. There is also some loss of volume in the left upper

zone but no lung nodules seen. A bone scan shows evidence of

degenerative changes but no specific evidence of bony metastases. Her

thyroid function tests show that the TSH is 0.12 and her free T3 are 4

which indicates that the TSH is slightly low. This does not amount to

primary hypothyroidism but it would be worth repeating the thyroid

function tests in three months time.

Overall, it appears that the patient has stable disease on Arimidex

apart from in the right supraclavicular fossa. The Arimidex is not

holding the disease completely and we feel that the best approach to

management would be to consider some radiotherapy to the right

supraclavicular fossa. She has previously had radiation therapy to the

left clavicular region and mediastinum. We have discussed performing a

CT scan of the thorax but she was unable to lie flat for the duration

of the investigation some months ago. We shall ask our radiotherapy

colleagues to review her and consider her for therapy. We shall review

her again in the follow up clinic in six weeks time.

28/03/2003, 10:50:25

ROYAL MARSDEN NHS TRUST - PATIENT CASE NOTE

######:MRS ##### #######

24 Jan 1997 Seen in the Chemotherapy Clinic (TPFRIDAY)

I saw ##### today in clinic. I am very pleased to say that she has had

a complete response in her superior mediastinum and right

supraclavicular fossa lymphadenopathy. There is some minimal thickening

remaining in the soft tissues around the superior mediastinum and in

fact it is felt that this might now be related to previous

radiotherapy. To be honest, however, symptomatically there has been

little in the way of benefit with overall palliative response of no

change. She is tolerating the treatment fairly well. Interestingly she

has had virtually complete alopecia with the treatment. She has been on

warfarin for about the same amount of time and I wonder whether this

may be partly responsible. We have given her a fourth cycle of

treatment today and we will see her in three weeks for consideration of

her fifth.

28/03/2003, 10:44:20

ROYAL MARSDEN NHS TRUST - DIAGNOSTIC RADIOLOGY - CT REPORT

######:#######,MRS #####

Exam 18 Dec Examination LIVER/THORAX/ABDOMEN/PELVIS

Exam Number [NUM]

Date of Birth 17 May 1933

Ref [HCA1] OUTPATIENT

Clinical

BR Verified by [HCA2]

DIAGNOSIS: Carcinoma of breast.

CT scans have been obtained through chest, abdomen and pelvis with oral

contrast only.

There is thickening in the left clavicular fossa and small-

volume residual abnormalities in the mediastinum. Comparison is made

with the most recent scan (21.7.95) and there is no discernible change

by CT criteria.

Lung changes, which may have been related to radiotherapy, are now less

extensive.

There are no abnormally-enlarged nodes in the retroperitoneum

or pelvis. There are no focal hepatic masses.

CONCLUSION: No CT evidence of disease progression.

28/03/2003, 12:35:06

疾病診斷Consider a 62-year-old man with 3 months

history of severe back pain. His weight remained stable. CBC and routine biochemistry were normal. ESR was 52 mm / hour. An x-ray of the lumbar and thoracic spine was reported to showing degenerative changes. Cancer

Low back pain

History and physical examination

History of Previous cancer

Age > 50 years or Failure of treatment or

weight loss

No significantfinding

ESR

ESR < 20 and only one clinical Finding

ESR > 20 or more than one clinical finding

ESR,spineFilms, 9%

with cancer

No cancer

X-ray2.3% cancer

特徵

What was What was donedone……

What happened…What happened… And whyAnd why

Human:1382

Mass:1666

locus

Pain:5735

locus

locus

locus

Ulcer:1945

Cancer:1914

Breast:1492

locus

Radio:1812

plansplans

Chemo:6502

plans

Clinic:4096

Biopsy:1066

Clinic:1024plans Clinic:2010plans

target

attends

attendsattends

treats

treats

finding

finding

reason

reason

reason

reason reason

reason

time time time time time time time time

Concept Lattice

C1:(D1,Ø)

C2:({d1,d2,d4},{t1,t6}) C3:({d3,d4},{t4})

C4:({d1,d2},{t1,t3,t5,t6})C5:({d4},{t1,t4,t6})C6:({d3},{t2,t4})

C7:(Ø, T1)The formal conceptC4 has two own terms{t3,t5} and two inheritedterms {t1,t6}

Given the context (D1,T1) whereD1 = {d1,d2,d3,d4} & T1 = {t1,t2,t3,t4,t5,t6}

R t1 t2 t3 t4 t5 t6d1 1 0 1 0 1 1 d2 1 0 1 0 1 1d3 0 1 0 1 0 0d4 1 0 0 1 0 1

Table: The input relation R = documents keywords

Hasse Diagram

Text Analysis Spectrum

Entity Extraction

Targeted Factsand EventsClassification

Clustering

ConceptIdentification

What is thisdocument about?

Who didwhat towhom whenwhere, etc.

Why is getting dimensional data so hard?

Hank bought plastic explosives from Henry inTucson yesterday.

Named Entity Extraction

People,Weapons,Vehicles,

Dates

NEREngine

HankHenry

Plastic explosives

Tucson11/01/07

Automatic Pattern-Learning Systems

Pros:Portable across domainsTend to have broad coverageRobust in the face of degraded input.Automatically find appropriate statistical patternsSystem knowledge not needed by those who supply the

domain knowledge.

Cons:Annotated training data, and lots of it, is needed. Isn’t necessarily better or cheaper than hand-built sol’n

Examples: Riloff et al., AutoSlog, Soderland WHISK (UMass); Mooney

et al. Rapier (UTexas); Ciravegna (Sheffield) Learn lexico-syntactic patterns from templates

Trainer

Decoder

Model

LanguageInput

Answers

AnswersLanguageInput

P14 performed

P11 participated in

P94 has created

E31 Document

“Yalta Agreement”

E7 Activity

“Crimea Conference”

E65 Creation Event

*

E38 Image

P86 falls within

P7 took place at

P67 is referred to

by

E52 Time-Span

February 1945

P81 ongoing throughout

P82 at some time within

E39 Actor

E39 Actor

E39 Actor

E53 Place

7012124

E52 Time-Span

11-2-1945

Explicit Events, Object Identity, Symmetry

Rules ExtractionThe formal concept C4 makes it possible

the following rules R1 : t3 t1 t6R2 : t5 t1 t6R3 : t3 t5

The interpretation of the R1 and R2: The use of terms t3 or t5 is always associated with that of terms t1 and t6

The rule R3 express mutual equivalence of the terms {t3,t5}: All the documents which have the term t3 also have the t5 term.

中低收入戶補助

因果圖 -- 失依兒童

各縣市福利，信託基金的

成立

所在各縣市失依兒童狀

態

各縣市政府，社會局等介入

對單親家庭的補助之災後重建及經費相關使用

災後重建基金

規則

中文 NER – Example 2 黑色當道少了尖叫女星太規矩城城活跳跳金馬獎星光大道不若前晚金鐘獎

「峰芒」畢露，女星們規矩平穩的服裝，讓星光大道上少了一些特色，並未出現讓人眼睛一亮的驚喜。其中，在金鐘獎上讓人血脈僨張的蕭淑慎，在金馬獎上可以看出服裝「規矩」了些。總體來說，今年的星光大道造型略顯平庸。秋冬主流黑色更在金馬星光大道上大量出現，凱渥模特兒公司老闆、也是專業資深時尚人洪偉明說：「可以發現他們選擇合適的服裝，規矩、正式的選擇，可避免遭受批評，今年確實少了些特色，但重要的國際場合，平穩的黑色服裝，也是出席正式場合的安全造型。」洪偉明表示：「楊千嬅的服裝和她的人很搭，黑色蕾絲讓她不至於顏色過重，正式中又帶點活潑，感覺很棒。」台中市長胡志強女兒胡婷婷桃紅色的緞面禮服，也讓洪偉明很欣賞，他說：「整體感覺落落大方，亮色服裝和她的人也很適合，她的自信和星光大道主持人蔣怡的乾淨大方一樣，讓人感覺舒服，也是不錯的造型。」舒淇鵝黃色的禮服，洪偉明笑說：「羅曼蒂克的感覺和她的笑容很搭配，讓氣色宛如戀愛中的女人一樣美好。」梁詠琪的黑色短禮服，雖然露出她的修長美腿，但洪偉明也建議：「她至少可以搭雙絲襪，整體感覺會更好。她在演唱會上展現性感，其實星光大道上也可以大膽改變。」至於男星們的服裝，今年則是絲絨的天下，洪偉明笑說：「男星們服裝不易做出變化，敢大膽嘗試不同造型的人也不多，其中郭富城神采奕奕的精神，十分突出，張震的服裝則顯得穩重而規矩。」

專有名詞詞詞類出現次數

張震 [Nb] 專有名稱 1

賴雅妍 [Nb] 專有名稱 1

米蘭 [Nb] 專有名稱 1

林熙蕾 [Nb] 專有名稱 2

楊貴媚 [Nb] 專有名稱 1

林志玲 [Nb] 專有名稱 1

楊采妮 [Nb] 專有名稱 1

藍正龍 [Nb] 專有名稱 1

侯佩岑 [Nb] 專有名稱 3

梁詠琪 [Nb] 專有名稱 2

黃子佼 [Nb] 專有名稱 1

楊千嬅 [Nb] 專有名稱 1

胡婷婷 [Nb] 專有名稱 2

戴起 [Nb] 專有名稱 1

詞詞類出現次數

背後 [Nc] 地方詞 1

中途 [Nc] 地方詞 1

世界 [Nc] 地方詞 1

天下 [Nc] 地方詞 1

原地 [Nc] 地方詞 1

舒淇 [Nb] 專有名稱 2

高達 [Nb] 專有名稱 1

白 [Nb] 專有名稱 1

竹幼婷戴榮賢 [Nb] 專有名稱 1

郭富城 [Nb] 專有名稱 1

范文芳 [Nb] 專有名稱 1

金馬獎 [Nb] 專有名稱 3

舒淇鵝 [Nb] 專有名稱 1

金城武 [Nb] 專有名稱 2

蕭淑慎 [Nb] 專有名稱 4

黃志瑋 [Nb] 專有名稱 1

天心 [Nb] 專有名稱 1

洪偉明 [Nb] 專有名稱 2

師李 [Nb] 專有名稱 1

時間詞詞類出現次數

昨天 [Nd] 時間詞 4

新春 [Nd] 時間詞 1

昨晚 [Nd] 時間詞 1

早春 [Nd] 時間詞 1

前晚 [Nd] 時間詞 2

先後 [Nd] 時間詞 1

今年 [Nd] 時間詞 6

週末 [Nd] 時間詞 1

詞詞類出現次數

露美腿 [LN] 人名類 2

台中市長胡志強女兒胡婷婷桃紅色

[LN] 人名類 1

Generative Discriminative

重建家園專案

金融機構

貸款震災重建暫行條例受災戶

房屋

利息

損毀

災戶object

method

Object:attribute

Object:attribute

Object:attribute Object:

condition

Object:attribute

Object:Attribute (condition)

Object:attribute

Specify

Generalize

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範例很適合用機洗香味好聞去污力強洗衣省力氣味清香能去除 99 種污漬洗得特別乾淨香味好聞白襪子洗得最乾淨氣味很香不傷手能夠很好的去除污漬衣服不易褪色洗衣不費力能去除 99 種污漬用量少洗得乾淨對皮膚刺激少洗各種污漬都很乾淨洗得乾淨價格適當洗衣服的效果較好氣味不錯一直使用該品牌洗好的衣物更白氣味好聞廣告印象深洗得乾淨易漂清不太傷手洗得乾淨用量少洗得乾淨用量比別的牌子少廣告大洗得乾淨用量少質量好用量少洗得乾淨包裝好廣告多，吸引人香味好聞洗的乾淨、白宣傳好，廣告有趣很多人都說好

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語意概念萃取 for Malignancy DSS

Bag of “Words”extraction

Patient IDPatient IDESRESR

severe severe back back painpainx-rayx-ray

lumbarlumbarspinespine

degenerative degenerative changeschanges

Expressionsextraction

Patient IDESRESR

severe back painsevere back painx-rayx-ray

lumbarlumbarspinespine

degenerative changesdegenerative changes

Named Entitiesextraction

Patient ID Diagnostic termmalignancymalignancy?

ESR screening test Lumber, Spine Anatomy Term

degenerative changesdegenerative changes Symptom Symptom

Events/SentimentExtraction

Patient (Patient ID) ESR Screening (Positive)Symptom (Positive Indication) Cancer

CombinedWith structured data

Decision Making

malignancy Treatment

Knowledge InferenceInformation ExtractionInformation Retrieval

( 文件 ) 資料探勘走向決策支援彙整同一性質資料 Clustering資料探勘以產生關聯相依規律 Association

Rules視覺化顯示協助專家研判主題 Visualization定義處理指引方便建立決策支援 Processing

Guideline

發展FTP Gopher HTML

CrawlingIndexingSearch

Local data

MonitorMine

Modify

Web Servers

Web Browsers

Social Network

of Hyperlinks

Relevance Ranking

Latent Semantic Topology

Topic Directories

More structure

Clustering

Scatter-Gather

Semi-supervisedLearning

AutomaticClassification

WebCommunities

TopicDistillation

FocusedCrawling

UserProfiling

CollaborativeFiltering

WebSQL WebL

XML