Table Of ContentStudies in Big Data 101
Herwig Unger
Mario Kubek
The Autonomous
Web
Studies in Big Data
Volume 101
SeriesEditor
JanuszKacprzyk,PolishAcademyofSciences,Warsaw,Poland
Theseries“StudiesinBigData”(SBD)publishesnewdevelopmentsandadvances
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other. The series contains monographs, lecture notes and edited volumes in Big
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·
Herwig Unger Mario Kubek
The Autonomous Web
HerwigUnger MarioKubek
LehrstuhlfürKommunikationsnetze FernUniversitätinHagen
FernUniversitätinHagen Universitätsstraße
Hagen,Nordrhein-Westfalen,Germany Hagen,Germany
ISSN2197-6503 ISSN2197-6511 (electronic)
StudiesinBigData
ISBN978-3-030-90935-2 ISBN978-3-030-90936-9 (eBook)
https://doi.org/10.1007/978-3-030-90936-9
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Preface
TheWorldWideWebbecamethemajorinformationsourceformanypeoplewithin
the last years; some even call it the brain or lexicon of mankind. For any arising
questions,anyfactsneededoranymultimediacontentwanted,awebpageproviding
therespectiveinformationseemstoexist.Likewise,itseemsthatsometimesthereis
nothingwhathasnotbeenthought,written,paintedorexpressedinanyotherform
before. In particular, for researchers and scientists, it is a fast deal now to retrieve
informationabouttheworksoftheircolleaguesandcheckwhetheranideaisnewor
alreadyappliedanywhereinthisworld.Geographicdistancesbecomemoreandmore
meaninglessbecauseofthisrapidexchangeofinformation,andtheworldappears
somehowlikeavillage.
Despite this still permanently growing amount of available information, its
managementstilldidnotchangemuchoverthepastdecades.Bigsearchengines,and
mostlyGoogleasamonopolistwithover90%ofusage,areneededtomapaninfor-
mation request to the right location (Uniform Resource Locator, URL), where the
respective information is found. Although hardware and search engine technology
hasrapidlyimproved,themajorprinciplesarestillthesame.Webpagesaredown-
loaded (copied), indexed and their main keywords or contents are stored in huge
(centralised and not always continuously updated) databases. This big amount of
datacanbeaccessedbyformulatingarequestwithafew,well-selectedkeywords,
whichwillresultinananswerinformofaplainASCIIlistwithlinkstomatching
contentsandsometimescontainingasetofpicturesandvideoswithfittingcontents.
Besidesthatinopportuneuserinteraction,thecurrentapproachesofwebsearchlead
toahighconcentrationoftoomanysensitiveinformationatafew,hugesearchengine
companiesandtransformtheusersintotransparentones,whoarepredictableinmost
oftheiractivitiesandaims.
Consequently, the need for any new technologies for the autonomous self-
management, more timely information handling and the user’s interaction with it
intheWebarises.Fromtheauthors’pointofview,thisproblemismostlyanaviga-
tionaloneforwhichalotofanaloguesareknown.Amazingly,themostcommonone
is the management and navigation in the street system of a country. Similar to the
Web,nobodyisabletooversee,knoworcontrolthestatusofallhighways,streets
v
vi Preface
andplacesinacountry,butapersonmayknowonlyher/hislocalneighbourhoods
quite well and is thus able to navigate perfectly in it. For any far-distance naviga-
tiontoplacesmanagedbyotherpeople(regions),onlyaroughorientationmightbe
possible.Aglobalsignpostsystemandafewglobalmapscanhelptofindtheright
directions there, while local people (knowledge) may help to orientate within the
conditionsofanothercity.Consideringthemainprinciplesofthemanagementand
functionalityofatrafficsystem,namelytheindependent,localmanagementaswell
astheuseoflocalknowledgeintherespectivesituation,thoseaspectsarethebasis
foraperfectlyworkingsystem.TheapplicationoftheseconsiderationsintheWorld
WideWebmeanstoalsorememberandfavourdecentralisedsystems’workingprin-
ciples:infact,iftheoriginalapproachoftheWebisconsidered,webserverswith
their linked and locally managed documents build exactly such a system but lack
anyrealandautomatednavigationpossibilities.Furthermore,therearenoefficient
mechanismstogroupsimilarorrelatedinformationina(maybehierarchic)manner
andmakeitaccessibletothehuman’stop-downorbottom-upthinking.
Atthispoint,theinterestedreadermayaskher-orhimself,whichorganisational
andfunctionalprinciplesderivedfromnatureandespeciallythehumanbrainmaybe
adaptedtorealisethedesired,newworkingprinciplesoftheWeb.Indeed,theauthors
ofthecontributionsinthisvolumeweregreatlyinspiredbyEinstein’ssaying‘Look
deepintothenature,thenyouwillunderstandeverythingbetter’.Therefore,manyof
thepresentedmethodsareinspiredbynatureaswellasphysicalorbiologicalcoun-
terpartsandarerealisedwithinacomputersystems’environment;themajoridea,the
text-representingcentroidtermsusedforcategorisationpurposeswerederivedasa
specialformofgeneralisedmediansfromthecenterofmassinphysics.Mostother
approaches follow the strict natural design principle of locality, i.e. work without
overseeing the whole set of data and structures and work with locally available
information,only.
ToexplainthisnewpointofviewontheWeb,thebookisstructuredasfollows:
(cid:129)
InChap.1,webrieflyreviewthestructureanddevelopmentoftheWorldWide
Web,whilespecialattentionisgiventothesearchandinformationmanagement
init.
(cid:129)
Chapter 2 discusses an approach for a new kind of locally working (medical)
recommendersystem,whichinparticularaimstosummariseandrepeatthemajor
ideas of the co-occurrence-based text mining and of course of the mentioned
text-representingcentroids.
(cid:129)
Basedonthisknowledge,Chaps.3–5presentthreeversionsofanew,fullydecen-
tralisedandintegratedwebsearchengine,whichrealisetheimaginationsofthe
authors and their co-workers to create a new kind of an underlying informa-
tion management for the Web. Another link-optimising information system is
presentedinChap.6asanalternativeformedium-sized,web-basedinformation
systems.
(cid:129)
Finally, Chaps. 7–11 explain the major but usually application-specific and not
easily accessible methods of our new information management approach. Due
toitsgeneralimportancewithrespecttogroupingandorderinginformation,two
Preface vii
chaptersareaddressingproblemsofclustering:afterasurveyinChap.7,alocally
working clustering algorithm is introduced in Chap. 8. Chapter 9 deals with a
specialaspectofdecentralisedroutingwithincompleteinformation.Lastbutnot
theleast,Chaps.10and11willpresentimportantaspectsofmodernknowledge
management:findingfrequentlyusedsequencesandapplyingatime-depending
informationmanagement(e.g.oblivion).
Atthispoint,theeditorswanttothankallresearchersofthe‘TeamofCommunica-
tionNetworks’fortheireffortandforfollowinganddevelopingourmaybestrangely
sounding,firstideasovermanyyears.Asaresult,manyworkingapplicationswere
implementedaswellaspublicationsandfinallythisbookwaswritten.Therefore,in
eachofthechapters,theauthorspresenttheirrecentworkresultsinashort,condensed
manner.
Allofuswishourreadersinspiringhourswiththisbook,andwewillbegrateful
for any responses and opportunities to present our works to the community of our
much-valuedcolleaguesallaroundtheworld.
Hagen,Germany HerwigUnger
August2021 MarioKubek
Acknowledgements
Bothresearchersareluckythatafterthefirstmeeting15yearsago,theywereable
to identify common research interests and, regardless of initial difficulties, found
acommonlanguage,commonresearchgoalsaswellasacommonvisionfortheir
work. In 2010, this resulted in the opportunity to research and teach together in a
team,whichisworkingtogetherforover11yearsnow.Supportedbymanycolleagues
andstudentsatalllevels,someofthemfromourpermanentresearchpartnerKing
Mongkut’sUniversityofTechnologyNorthBangkok(Thailand),thosedreamscould
berealisedstepbystep.Manyinspiringmoments,weeksofhardworkfollowedby
happinessordeepdepressionsaswellasdifficultiesofvariouskindstosolvewere
on our way. This book contains the summary and the reminiscences of what two
researchers and their team may achieve, if they feel the passion for research and
followtheirvision.Ontheway,weenjoyedeverysingleminute,werethankfulfor
every, often unexpected, help obtained and feel deeply sorry that this close, joint
workmighthavetocometoanendverysoon.
ix
Contents
1 State-of-the-ArtSurveyonWebSearch ......................... 1
GeorgP.Roßrucker
1.1 Introduction ............................................. 1
1.2 TheWeb ................................................ 1
1.2.1 StructureoftheWeb .............................. 1
1.2.2 EarlyApproachestotheUseoftheWeb ............. 3
1.3 TaxonomyofWebSearch ................................. 5
1.3.1 Intention ........................................ 5
1.3.2 Subject:OpenVersusClosedDomainSearch ......... 7
1.3.3 UseCase:QueryVersusContent-BasedSearch ....... 8
1.4 SupportingPillarsofWebSearch ........................... 9
1.4.1 ContentDiscovery ................................ 9
1.4.2 TextProcessingandKeywordExtraction ............. 11
1.4.3 TextMining ...................................... 12
1.5 SearchEngines .......................................... 15
1.5.1 ChallengesofWebSearch ......................... 15
1.5.2 RelevancePropagation ............................ 15
1.5.3 QueryAnalysis ................................... 16
1.5.4 DistributedSearch ................................ 17
1.6 Conclusion .............................................. 19
References .................................................... 21
2 A Concept for Recommender Systems Based
onText-RepresentingCentroids ................................ 25
HerwigUnger, MarioKubek, YanakornRuamsuk,
andAnirachMingkhwan
2.1 MotivationandBackground ................................ 25
2.2 FundamentalsofNaturalLanguageProcessing ............... 26
2.2.1 Text-RepresentingCentroids ....................... 26
2.2.2 InferenceMechanism ............................. 27
2.3 DesignExample:TheMedicalRecommenderSystem ......... 28
xi
