The Times They Are A-Changin' ­ The Corporate History Analyzer

The Corporate History Analyzer

Jurgen Angele b

,Hans-Peter Schnurr a,b

, Steen Staab a,b

,Rudi Studer a,b

E-Mail: fangele,schnurr,staab,studer g@ont opri se.d e

a

InstituteAIFB, University of Karlsruhe, 76128 Karlsruhe

http://www.aifb.uni-karl sruh e.de /WB S

b

Ontoprise GmbH,Haid-und-Neu Strae7, 76131 Karlsruhe,Germany

http://www.ontoprise.com

Comegather'roundpeople

Whereveryouroam

Andadmitthatthewaters

Aroundyouhavegrown

Andacceptitthatsoon

You'llbedrenchedtothebone.

Ifyourtimetoyou

Isworthsavin'

Thenyoubetterstartswimmin'

Oryou'llsinklikeastone

Forthetimestheyarea-changin'.

BobDylan,1963

Abstract

Up-to-date corporate information research,

i.e. the active tracking and management of

knowledgerelevanttoone'sbusiness,isama-

jor task for knowledge-intensive companies.

While the correct analysis of market situ-

ations and competitors are critical require-

mentsfor success, thefailure to provide ade-

quateknowledgeaboutone'sbusinessenviron-

mentmayincurlargelosses. Inorderto sup-

port thetrackingof externalbusiness knowl-

edge and its analysis, we have built CHAR,

theCorporate History AnalyseR,anew type

of system for gathering and analysing tem-

poral data about companies. CHAR inte-

grates facts about organizational structures

andstrategicactivitiesintoacommonknowl-

edge base. Building on an ontology with

an elaborate temporal structure, knowledge

Thecopyrightofthispaperbelongstothepaper'sauthors. Per-

missiontocopywithoutfeeallorpartofthismaterialisgranted

provided thatthecopies arenotmade ordistributed fordirect

commercialadvantage.

Proc.oftheThirdInt.Conf. onPracticalAspects

ofKnowledge Management(PAKM2000)

Basel,Switzerland,30-31 Oct.2000,(U.Reimered.)

http://sunsite.informatik.rwth-aachen.de/Publications/CEUR-WS/Vol-34/

pieces are amalgamated in order to derive a

plentitudeofsummarizingviews ontocurrent

andpreviousstatesofaairs.

1 Introduction

Global marketschangingwith aneverfaster paceare

oneof the key topics in business nowadays. Keeping

trackofwhatchangesinthemarketsandrecognizing

whatmovesone'scompetitorsisvitaltoanyenterprise

thatwantstosucceedonaglobalscale. Whilethishas

beenatruism formanagementat thetopmost strate-

gic level for a long time, the very same necessity is

currentlyspringinguponallmanagementlevelsdown

totheexpertknowledgeworkerwhomanageshisown

skills.

The trouble is that these management levels and

professionals do haveahard time gatheringinforma-

tion, analyzing it, and performing their operational

work,suchasresearchinganddevelopingnewproducts

or streamlining their production lines. This means

thattheevaluationofwhathappensinone'sownbusi-

nessmayoftenbeneglected.

Here comescorporate researchinto play. Thetask

of the corporate researchers is the tracking of rele-

vantknowledgeintheoutsidebusinesssettingandthe

communicationofimportantknowledgeto stakehold-

erswithin thecompany. The generaldiÆculty, then,

isthedeliveryofknowledgetotherightpersonsatthe

righttime and atthe right level ofabstraction. Peo-

pledoneitherwanttobeoodedwithfactsthat they

do not need nor do they want to be swamped with

nittygrittydetails,buttheyratherneedasummariz-

ingviewontothesinglepiecesofknowledge.

Withtheseaimsinmind,wehavedevelopedCHAR,

theCorporate History Analyzer, asystemthat allows

for collectivegatheringof information and forintelli-

edge at the appropriate level of abstraction. Thus,

CHAR constitutes an new typeof systemthat is in-

terestingfromtheapplicationaswellasfromthetech-

nical point of view. Seen from theside of theusers,

i.e. thecorporateanalystsandtheircustomers,itsur-

passesexistingsystemsregardingtherangeofsupport

itoersonthequeryingandontheprovisioningside.

Regardingthetechnicalbackground,itincorporatesa

rangeofontology-basedknowledgemanagementtools

thatareinterestinginthemselvesandwhicharecom-

bined to support a multitude of views based on an

ontologywithanelaboratetemporalstructure.

Intherest of thispaperwewillrst elaborate the

businesscasethatthehistoryanalyzermaybeusedfor

(cf. Section 2). Then we describethe views onto the

knowledgebasethatsupportcorporateresearchersand

theirco-workersandthatallowtheformer(orpossibly

bothgroups)to contributetotheknowledgebase. In

a nal step we describe how the overall system has

beenconceivedand implemented (Section 4). Before

we conclude, we give a short survey of related work

andrefertosomebusinesscasesthatarebasedonthe

samepremisesasourstudy,butwhichworkonabasis

muchlesssophisticatedthanCHAR.

2 A Case Study | Restructuring in

the Chemical Industry

ConsiderthecaseyouarekeyaccountmanagerofCol-

orBasic Inc, asupplierof basicmaterial forthe color

industry, responsible for several key accounts in the

EuropeancolorIndustry. Theotherdayyoureadina

newspaperarticle,thatoneofyourbiggestcustomers,

the German BigcolorAG is in acquisition talks with

theirfrenchcompetitorGrandcouleurS.A.

So what? Ina rst happyreactionaboutthis de-

velopment,youdiscusswithyourproductionmanager

theabilityofyourcompanytoincreasetheproduction

of basicmaterialin ashort timeperiod. Youplan to

convinceyourkeyaccountatBigcolorAGtoenhance

your supply agreement also for their new subsidiary

immediatelyafteraquisition. Niceanalysis! Yourpro-

duction manager conrms a possible increase of pro-

ductionandpreparesaquickswitchofproductionline.

Twomonthlater,youreadthenewsabouttheacquisi-

tionofGrandcouleurS.A.and immediately,youmeet

yourkeyaccountatBigcolorAGtogethisagreement

forhighersalesvolumeofbasicmaterialwithveryex-

ibledeliveryconditions. Nicestrategy!

Yourkeyaccountisimpressedaboutyourquickre-

action and your fast and exible supply conditions,

buttellsyou,thatBigcolorAGacquiredGrandcouleur

S.A.duetothefactthattheyhaveasubsidiaryinthe

basicmaterialindustry,GrandBasicInc.,yourbiggest

integration and bought very interesting supply con-

ditionsviatheacquistionofGrandcouleurS.A.Thus,

unfortunately,insteadofhighersalesvolumeyouwont

haveanysales in near future with BigcolorAG. Bad

News!

Now, it is easy to recognize, that your analysis of

the situation waswrong. You had notenough infor-

mationabouttheacquisitionto createabetterstrat-

egy. Later on,youwill hearalotofcolleagues telling

youstoriesaboutthewell-knownrelationshipbetween

Grandcouleur S.A.and GrandBasicInc. Evenworse,

but howshouldyouhandle such situations? There is

aneverfasterpaceofchangeinglobalmarkets. There

is no day without news about mergers, acquisitions

and alot of otherstrategic movesof playersin every

industry. Oneofthemostdynamicmarketsinthepast

yearshasbeenthechemicalindustry. Here,bigglobal

playerspermanentlyrestructuretheirorganization,try

toacquiresmallinnovativetechnologyleadersorght

aboutentrystrategiesin newmarkets. This verydy-

namicsituation leadstotheproblem, thatnomarket

participant has a permanent clear picture about the

industry.

Nowadays,themarketanalysts,consultantsandin-

house market research departments try to track the

activities of their industry with traditional methods.

Newspaperarticles,onlinedatabasesandannualcom-

panyreportswereanalysedandcompetitorswebpages

werethoroughlytracked. Theresultsarepresentedto

themanagement,publishedinreportsanddistributed.

Thereexist severalproblemsinthis researchprocess:

Information archivesare document-based. For a

collectivegatheringoffactsthisviewistoocoarse.

Bythis way onemay introducean abundanceof

redundancies on the one hand and one may ac-

countfor onlyfewofmanyaspects thatoccurin

aparticulardocument(e.g. onlytheinformation

given in the headlines), thus missing the crucial

piecesofinformationagain.

Thenextproblem stemsfrom thefact thattypi-

cally documentmanagementsystemsrelyalmost

exclusively on information retrieval techniques,

whichareratherunreliable.

Even if convential annotation is used for these

documents, it is most often too cumbersome to

describe the relevant implications, too. E.g., if

one company sells one of its units, the implica-

tion is that this unit may no longer be the sole

supplierfortheoverallcompanyasitwasbefore.

Theseimplicationsmayonlybemadetransparent

if background knowledge is used, but document

thesauri|themostadvancedones employtopic

maps.

Finally, dierent executives need dierent views

ontothesamebasicpiecesofinformation. What

is relevant to the oneemployee, e.g., acompeti-

tor's expansion in his regional market, may be

irrelevantfromamoreglobalpointofview.

Thus, what wewantedto havewasasystem that,

(i), supports the collective gathering of information

ontheleveloffacts ratherthandocuments,(ii), inte-

grates the gathering tasksmoothlyinto thecommon

research process, (iii),allowsto intelligently combine

facts or givea high-level view, e.g.,a summarization

ora statement abouta generaltrend, about awhole

setoffacts,(iv),checksnewfactsagainsttheavailable

backgroundknowledge,(v),allowsamultipleviewac-

cess to the knowledge via asingle entry portal, and,

(vi), allowsto route derived facts backinto the com-

monworkplaceenvironment.

Additionally, in our specic business process, we

wantoursystem toimprovethequalityandspeedof

theknowledgegatheringanddistributionprocessin a

companysresearchdepartment. Thereforewehaveto

assureanintuitivegraphicaluserinterface,tailoredto

thespecicuserneeds.

Beinggiventhissystem,thekeyaccountmanagers

ofColorBasicInc. couldhavereallyprotedfrom the

workdonein his company'sresearchdepartment. He

would have seen the strategic implications following

fromtheacquisitionofGrandcouleurS.A.byBigcolor

AG.ThesystemwouldhaveusedthefactthatGrand-

Basic Inc. is asubsidiary of Grandcouleur S.A. and,

thus, aprobablesupplierforBigcolorAGin order to

deriveaverticalintegrationasapossibleobjectivefor

theacquisition.Hence,thekeyaccountmanagercould

havedonetherightthings.

3 CHAR | The system

Intheprevioussectionwehaveseensomepitfallsthat

may appear while tracking one's markets and com-

petitors. From these problems we have derived the

requirementsthatasystemforcorporatehistorytrack-

ingshould meet:

1. It should provide multiple views onto the

same knowledge base for dierent time frames,

for dierent regional foci, for varying intra-

organisationalstructuresandfor dierentstrate-

gicquestions,tonamebutafew.

2. It should allow many people to contribute fac-

tual knowledge in a way that is embedded into

aroundasemanticbackground.

In this section we elaborate on these two require-

ments in Subsections 3.1 and 3.2. Thereby, we

only summarize the second part as it is composed

of parts that we have already described elsewhere

([EMSS00,SS00,SAD +

00]).

Thereadermaynoteherethatthemechanismsde-

scribed here rely on a common conceptualization of

thedomain,anontology. Thisandsomefurthertech-

nical assumptionswill beexplained in moredetail in

Section 4.

3.1 Querying Knowledge

ThequeryinterfaceoftheCorporateHistoryAnalyzer

has been developed in order to deal with organiza-

tional and strategicquestions that depend onspatio-

temporal constraints. It renders views that may be

seen ona commonweb browser. Actually, they look

just like common web sites with some choices for se-

lection. These selections are also controlled by the

knowledge of the backend system, e.g. one can only

selectcompaniesthatareknowntoexistintheknowl-

edgerepository.

Figure 1 depicts the main views that are oered

by CHAR, viz. Activities, Organization, Know How,

Strategic Questions and General Query Possibilities

(indicated by \Search"). While the latter may be

asked by means such as known from standard tools

for OLAP/business intelligence, we consider to help

the userwith the corporate historyanalyzer through

views that directly reecthis interestsontheorgani-

zationalandstrategiclevel.

3.1.1 Answer organizationalquestions

Therstmajorcategoryofqueriesrelevanttothecor-

porate historyis aboutorganizationalstructures and

the activities that change organizational structures.

Forinstance,theviewof\acquisitionsofM.A.Hanna"

returnsallitspurchases(cf.Fig.2),andcorresponding

viewsareoeredforSellings,Mergers,Restructurings

andManagementChanges(Figure1).

Whatisinterestingtonoteatthispointisthatitis

rather diÆculttoget aclear pictureof what isreally

happeningwith M.A.Hanna. Itis diÆcultandtime-

consumingforthehumananalysttodetectsometrend

inlistsofsinglefacts. Observationsbecomemucheas-

ier, when dierent typesof facts may berelated and

contrasted. For instance, Figure 3depicts twosnap-

shots of M.A.Hanna's organigramthat areautomat-

ically derived from single activities, like acquisitions

and restructurings, and that give the analyst a neat

picture ofhow formerlyisolated purchases that M.A.

inthecompanyin1997(e.g.,\CompoundingTechnol-

ogy"havingbeenreorganizedintothe BusinessArea

\PlasticCompounding").

It shouldhavebecome clearthatthis typeof com-

prehensivesupport isbeyondthescopeofstraightfor-

warddatabasesolutions,butratherrequiresextensive

programmingorthetypeof mechanismsthatwerely

onforCHAR|describedin detailinSection 4.

3.1.2 Answer strategic questions

This far, we have described how CHAR provides so-

phisticated supportthatisbasedon\hardfacts"and

that does not aim at interpretation of single facts.

With itssupport for strategic questions,CHAR tries

to give answersto questions aboutbusiness competi-

tors which cannot be answereddenitely, but which

rely onsomeconjectures. For instance, thepurchase

ofacompanyfromabroadmayleadtoagainofmar-

ket sharein that area,andthusto aregionaldiversi-

cation. Thus, the rst question in in Figure 4 is a

prototypestrategicquestion. Theoveralllistthat we

currentlysupport readsas:

1. Which Activityof Xleadstooperation inregion

Y?

2. Is there any regional expansionof X due to any

acquisitionsinceT?

3. Is there any regional expansionof X due to the

acquisitionofY?

4. Whatactivityof XmodiedtheirBusinessArea

Y?

5. WhatexperiencegainsX fromacquisitionofY?

Answersfor someof these questions are presented

in thelower partof Figure 4. Forexample, Hanna's

acquisition of Bergmann in 1994 led to anew opera-

tionin WesternEurope|exploiting thebackground

knowledgethatBergmann'sGermanbaseliesinWest-

ern Europe(lower left of Figure 4). Question 2trig-

gersasearchforanykindofregionalexpansionwithin

some time frame, which may be answered positively

withthecaseofEnviroCareCompounds(middle),Fi-

nally, Hanna's business areaof PlasticCompounding

wasaected byrestructurings such astheone of the

companypartthatformerlywasBergmann.

By now it should be obviousthat for this type of

questionsoneneedscomprehensivereasoningsupport,

suchasrulesaboutgeographicrelationships(Japanis

inAsia,ItalyisinSouthernEurope,etc.),rulesabout

categorization of know how, as well as rules about

strategic indications (purchase may be indicative for

regionalexpansion).

Finally,theinformationseekermayalsouse ourtree-

basedandhyperbolicinterfaces(cf.[SAD +

00])tocom-

pile\arbitrary"questions. These questionsmaycom-

prise conceptual and relationalrestrictions according

tothesystem'sontologyand/orregularexpressions.

3.2 Providing Knowledge

The process of providing new facts into the knowl-

edge warehouse should be as easy and as smoothly

integratedintothecommonworkingtasksaspossible.

Forthisreasonweoervariousmodesofcontributing

knowledge.

First, one mayenter information through aform-

basedinterface that isextended byacanonicaland a

hyperbolic tree view onto the concept hierarchy (cf.

[SAD +

00]).

Second, when the information that is to be pro-

vided is produced during the writing of documenta-

tions or reports onemayuse atemplate approach in

order to generate knowledge by writing these papers

(cf.[SS00]).

Third, one may use wrapper mechanismsin order

to providedatafrom tablesand listsontheweb. For

instance, the approach described in [BD99] uses the

same basicrepresentation (viz. F-Logic, cf. next sec-

tion)asitssemanticbackboneandmay,thus,directly

feedinto ourknowledgebase.

Fourth|andmostimportantforCHAR,onemay

use our annotationtool in order to add metadatato

data given in documents(cf. [EMSS00]). A snapshot

oftheannotationtoolnotingsomeactionaboutM.A.

Hannaisshownin Figure5: Theuserreadsorworks

with documentsusing atext orspreadsheet process-

ingtooloraninternetbrowser. Whenhedetectssome

relevantchange beingdescribedin thedocumentand

thischangemightbecomerelevant 1

,hehighlightsthe

wordor phraseandusestheannotationtooltoselect

the typeof the phrase(e.g. \Hanna M.A." isa com-

pany) and its relation to other material (e.g. Hanna

sells ShapesDistribution Business to GE Plastics on

May11, 2000). Thedocument,these factsand meta-

dataabouttheannotater,thetimeofannotation,etc.

isall storedin theback-enddatabase. Currentlythis

is apurely manual process. Inthe future weplan to

useinformationretrievalmethodstorecognizephrases

(or words) that had been seenand annotatedbefore

(e.g., if there is a second document about \Hanna

M.A.")andinformationextractionmethodsthat pro-

1

Our rst intuition was that every major organizational

change of one'scompetitorsor clientsshouldbenotedbythe

company'sITresearchdepartment. Overtimethisroughesti-

mationwillhavetobespeciedmoreprecisely|alsodepending

onthetypeofchangeanditsnancialimplication.

01.10.93

01.04.97

Figure3: Beforeandafterrestructurings

pose typesand relations between objects forannota-

tion. Also right now, we are starting to test inter-

annotatoragreement,butduetothecomplexityofthe

task, we believe, the application will always require

users who are trained with the system, the domain

anditsunderlyingontology.

4 Developing CHAR

Starting fromtheprincipleproblem(Section1), from

scenariossuchasseeninSection2,andfromusecases

such as described in the previous section, the ques-

tion was howto bring the requiredconceptual struc-

tures and reasoning capabilities into action. To an-

swerthis question,we heredescribehowwehaveap-

pliedourgeneralmethodologyfordevelopingontology-

based systems to corporate history analysis (Subsec-

tion4.1)includingtheontologyengineeringpart(Sub-

section 4.2) as well as the interface and integration

issues(Subsection4.3).

4.1 The DevelopmentProcess

We distinguish dierent phases in the development

process thatareillustratedin Figure6. Forthemain

part this model is a sequential one. Nevertheless, at

eachstagethereisanevaluationastowhetherandas

to howeasily further development may proceed with

thedesign decisionsthathavebeenaccomplishedbe-

fore. The resultsfeed back into the results of earlier

stages ofdevelopment. Themain stagesof thedevel-

opmentprocessandtheirkeycharacteristicsaregiven

in thefollowing:

User requirements are collected in the require-

mentselicitationphase. Resultsof thisveryrst

phase constitute the input for the design of the

websiteandforpreliminaryHTMLpagesandin-

uencetheformaldomainmodelembodiedinthe

ontology.

In parallel to the development of the structure

andlayoutofthewebsiteanontologyengineering

processisstarted. Anontologydenesacommon

languageandschema usedto structure, ndand

exchangeknowledgeaboutthedomain. Forthese

purposes interesting concepts together with at-

tributesandrelationsbetweenconceptsareiden-

tied and represented. Thereafter, rules are de-

veloped. Rules describe more abstract dynamic

relationsbetweenobjectswhichareusedtoderive

new objects, attributes orrelations that are not

given explicitely. Developing the ontology con-

taining static parts (concepts, attributes, roles)

and dynamic parts (rules) is thecentral issue in

developing such an application and is described

forourcaseathandinmoredetailinSection4.2.

In the query development step the views and

queriesdescribedin oneof theearlierphasesare

formalized. At rst, theirfunctionality is tested

independentlyfrom the website design in evalu-

atingthoseformalizedqueriesusingtheontology

andtestfacts.

Finally,webpagesarepopulated,i.e. thequeries

and views developed during website design, and

formalizedandtestedduring queryformalization

areintegratedintoqueryinterface.

After this core development process information

is provided to the knowledge base by the tools

mentionedinSection 3.2,i.e. byannotatingdoc-

uments,bydirectlyprovidingfactsusingthefact

editor etc. This process also runs in parallel to

theuseofthesystem.

4.2 Ontology engineering

The ontologyfor this application consists of (i) con-

cepts dening and structuring important terms, (ii)

their attributes specifying properties and relations,

and (iii) rules allowing inferencesand the generation

of newknowledge. The languageweuse to represent

this ontologyis F-Logic[KLW95],whichprovidesad-

equate modeling primitives integrated into a logical

framework. WeuseourtoolOntoEdit[SM00] toedit

thisstaticpartof theontologygraphically.

One speciality in this domain is that time issues

have to be modeled. There are many objectswhich

havea life time. Forinstance acompany hasastart

timewhenitisfoundedandthereisanendtimewhen

this company is acquired by another company or is

mergedwithanothercompany. Sodurationshadtobe

modeled. Likewise,anAcquisitionisanEventwhich

occurs at a specic time, which leads to the model-

ing of Timepoints. Thefollowingexampleshows the

modellingof AcquisitionsasActivityswhichitself

areeventsin F-Logic. Theattribute occursAtrepre-

sentsthetime point. Activityhas therolesubject

which representsthecompanyexecuting theactivity.

Acquisitionhasthepropertiespriceandshareand

therolehasObject,whichrepresentstheCompanyPart

theactivityappliesto.

Event [occursAt => Timepoint].

Activity::Event [subject => CompanyPart].

Acquisition::Activity [

hasObject =>> CompanyPart;

price =>> NUMBER;

share =>> NUMBER ].

Oneofthekeycharacteristicsofthisapplicationwas

thattheuserprovidesfactsaboutnewactionslikeac-

quisitions and mergersto the systemand the system

derivestheconsequences. Forthispurposeruleshadto

bemodelledforallpossibleactivitieswhichincursuch

consequences,forinstance \If acompany isrenamed,

it remains the same company but from this timepoint

onthiscompanyhasthenewname",\Iftwocompanies

are merged, anew company with a new name is cre-

ated, the old companies disappear, they arefromnow

onsubsidiariesofthenewcompany",\Ifacompanyis

acquiredbyanothercompanywithshare100%thenthe

rstonedisappearsatthistimepointandthenbelongs

tothesecondone",or\Ifadivisionisoutsourceditbe-

comespartofanewcompanyoritbecomesacompany

on itsown".

Alltheseexamplesshowthatthemodellingoftime

isacentralissueinthisapplication. Modellingoftime

hasnon-monotonic eects. Forinstancewhen acom-

panyisfoundeditpotentiallylivesforever. Butifitis

lateracquiredbyanothercompanyitslifetimeends.

Inadditiontothemodellingoftheeect ofactions

possiblestrategical consequenceshad to be modelled

byrules. Forexample,\Acompanywhichhasnoexpe-

rience in acertaintechnology and which acquires an-

othercompanywhichhas inventedthistechnologymay

have the strategy to become technology leader in this

area" or\A company which has no basein acertain

region andwhich acquiresanother company which op-

eratesin this region may have the strategy to expand

intothis region".

4.3 Glueing allparts together

During website design the presentation strategy and

actual layoutsare developed. Inthe queryformation

phase, queries are developed which deliver the infor-

mation. Insteadofexpressingthosequeriesdirectlyin

F-Logic,itismoreconvenienttouseourQueryBuilder

tool. Inadditiontothegraphicaldenitionofqueries

it provides output templates for the answers. These

templatesmaythenbeusedasstartingpointsforthe

developmentofthenalpresentationoftheanswersto

the user. There arealso templates for selectionlists,

radioboxesorchecklists,whichmaybeusedasinitial

settingsofHTMLform elds.

Inthecasethatauserhastoclicktoaxedquery

without providing further information such a query

maybeintegrateddirectlyinto thewebpageasahy-

pertextlinkbycopyandpastefromtheQueryBuilder

toolinto theHTMLeditor.

Inthe othercasethat auserhasto lloutaform

which then generates a query, this query has to be

created out of the contents of the form elds by a

Javascript program. E.g. thequery that returns the

names N of all companies C at time t (t is between

startandendtimeofthecompany)maybeexpressed

in F-Logicby:

FORALL N,C, ST,ET <-

C:company[name->>N] AND

starts(C,ST) AND

ends(C,ET) AND

ST <= t < ET.

Theuserhastoprovidetimetinaformeld. The

Javascript programhas to read thetime t outof the

form eld, hasto generate thequery asastring, has

toaddtheurlofthewebpagetheanswersarefedinto

andsendittotheunderlyingknowledge-basedsystem,

which in our case is the Ontobrokerinference engine

[DEFS99].

5 Related Work

Inthebusinesscommunityvariousapproachesareused

to analyze the development of markets and the be-

haviour of competitors. Portfolio analysis [Por92] is

oneofthemostpopularmethodsthatareused. CHAR

is well-suited to support portfolio analysis since this

method depends onanup-to-dateandcomprehensive

collectionofinformationaboutthebehaviourofcom-

petitors, a process that is considerably improved by

CHAR. Furthermore, the rules that are available as

part of the background knowledge assist in deriving

(strategic) conclusions about the behaviour of these

competitors.

Corporateresearchitselfisalsoanimportantbusi-

ness area. A large collectionof companies oersuch

researchservices. Typically,theprovidedinformation

isstored in databasesthat canbeaccessed viadier-

entindices. E.g. TheDialog Corporationoerssuch

databases addressing among others mergers and ac-

quisitions [DIA00]. However, these databasesdo not

provideanylinkingbetweenthedierentM&Aactions

nor dothey derive additionalinformation from these

facts. Reuters Business Brieng [DJR00] is oering

abroadcollectionofservicesincluding alsohistorical

information about companies. These servicescan be

integrated into an intranet environment thus provid-

ing access to these services at the workplace of the

knowledgeworker. Nevertheless,theseservicesdonot

speciedfacts. Inthe samewayHopenstedt [Hop00]

is oering a large collection of company information

either in online databases or as CDs. Compared to

thesecommercialservicestheCHARsystemisunique

with respect to its integration and interlinking of in-

formation and the inference capabilities for deriving

newknowledgefromthegivenfacts.

Consideringthetechnicalpart,thereexist,e.g.,nu-

merous publications about handling temporal infor-

mation. For instance, the Later system for manip-

ulating and querying a temporal knowledge base is

described by Brusoni et al. [BCTP97]. Later oers

operationstoassertanddeletefactsthatspecifyqual-

itativeandquantitativetemporalrelations. However,

temporalreasoningthatincludesthehandlingofnon-

monotonicityisnotsupported byLater.

In [BFG98] a generaloutline ofan ontology-based

approach to knowlege management is given. There,

three subtasks are described: ontological engineer-

ing,characterizingtheinformationsourcesintermsof

theontology,andintelligentknowledgeretrieval. The

CHAR system showshowthis general approach may

beinstantiatedtoanintelligentKMsolutionandhow

thesethreesubtasksarecarriedoutbypowerfultools.

An intelligent search facility for documents is de-

scribed in [SSHHS98]. They use the so-called Q-

Technology for classifying documents and oering

intelligent retrieval mechanisms. However, the Q-

calculususedinthisapproachisfarlesspowerfulthan

Frame-logicas used within the CHAR system. Fur-

thermore,theCHARsystemdeliversknowledgepieces

asanswersto posed queries,whereasthe systemout-

lined in [SSHHS98] delivers documents as query re-

sults.

6 Conclusion

Nowadays, markets are changing faster and faster.

Therefore, the need to analyze the changes that oc-

curin amarketincreasesdramatically. Conventional,

document-based approaches do not meet the needs

anymore: dierent pieces of information have to be

linked to each other and related to the background

knowledgeaboutgeneralmarketbehaviour.

CHAR(CorporateHistoryAnalyzer)isaknowledge

management system supporting the research process

withinacompany. Itisanintelligentassistant-typeof

system for keepingtrack of mergers and acquisitions

in a specic market and for providing advice about

strategic implications that can be drawn from these

M&A activities. More specically, CHAR provides

means for (i) a decentralized information provision-

ing process - by using a template approach and of-

fering an annotation tool, (ii) collecting information

the knowledge base, (iii) relating these pieces of in-

formationtotheavailablebackgroundknowledge,and

(iv) deriving consequences that followfrom these ac-

quiredfactsandthebackgroundknowledge-byapply-

ing (non-monotonic) reasoningtechniques. Basedon

these techniquesCHAR is oering integrated results

tovariouskindofqueriesincludingsummarizationsor

trend analyses. These functions are built on top of

the collectionof methods and toolsas oered by the

Ontobrokersystem[DEFS99]andtheSemanticCom-

munityWebPortalframework[SAD +

00].

Future work will aim at providing better support

forextractingrelevantpiecesofinformationfromvari-

oussources: acombinationoflinguisticandontology-

basedmethodswillprovidesemi-automaticmeansfor

informationextraction. Arststeptowardsthisdirec-

tionisdescribedin[EMSS00]. Anotherlineoffurther

research will bethe integrationof the CHAR system

intotheSmartTaskSupportapproach[SS00]thuspro-

vidingassistance forresearchersattheirworkplaces.

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