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Text mining is an exciting application ?eld and an area of
scienti?c - search that is currently under rapid development. It
uses techniques from well-established scienti?c ?elds (e. g. data
mining, machine learning, infor- tion retrieval, natural language
processing, case-based reasoning, statistics and knowledge
management) in an e?ort to help people gain insight, und- stand and
interpret large quantities of (usually) semi-structured and unstr-
tured data. Despite the advances made during the last few years,
many issues remain unresolved. Proper co-ordination activities,
dissemination of current trends and standardisation of the
procedures have been identi?ed, as key needs. There are many
questions still unanswered, especially to the potential users; what
is the scope of Text Mining, who uses it and for what purpose, what
constitutes the leading trends in the ?eld of Text Mining -
especially in relation to IT - and whether there still remain areas
to be covered. Knowledge Mining draws upon many of the key concepts
of knowledge management, data mining and knowledge discovery,
meta-analysis and data visualization. Within the context of
scienti?c research, knowledge mining is principally concerned with
the quantitative synthesis and visualization of - search results
and ?ndings. The results of knowledge mining are increased
scienti?c understanding along with improvements in research quality
and value. Knowledge mining products can be used to highlight
research opportunities, assist with the p- sentation of "best"
scienti?c evidence, facilitate research portfolio mana- ment, as
well as, facilitate policy setting and decision making.
The world of text mining is simultaneously a minefield and a gold
mine. It is an exciting application field and an area of scientific
research that is currently under rapid development. It uses
techniques from well-established scientific fields (e.g. data
mining, machine learning, information retrieval, natural language
processing, case based reasoning, statistics and knowledge
management) in an effort to help people gain insight, understand
and interpret large quantities of (usually) semi-structured and
unstructured data. Despite the advances made during the last few
years, many issues remain umesolved. Proper co-ordination
activities, dissemination of current trends and standardisation of
the procedures have been identified, as key needs. There are many
questions still unanswered, especially to the potential users; what
is the scope of Text Mining, who uses it and for what purpose, what
constitutes the leading trends in the field of Text Mining
-especially in relation to IT- and whether there still remain areas
to be covered."
Web Personalization can be de?ned as any set of actions that can
tailor the Webexperiencetoaparticularuserorsetofusers.
Toachievee?ectivepers- alization,
organizationsmustrelyonallavailabledata, includingtheusageand
click-stream data (re?ecting user behaviour), the site content, the
site str- ture, domainknowledge,
aswellasuserdemographicsandpro?les. Inaddition, e?cient and
intelligent techniques are needed to mine this data for actionable
knowledge, and to e?ectively use the discovered knowledge to
enhance the users' Web experience. These techniques must address
important challenges emanating from the size and the heterogeneous
nature of the data itself, as
wellasthedynamicnatureofuserinteractionswiththeWeb. Thesechallenges
include the scalability of the personalization solutions, data
integration, and successful integration of techniques from machine
learning, information - trievaland?ltering, databases,
agentarchitectures, knowledgerepresentation, data mining, text
mining, statistics, user modelling and human-computer - teraction.
The Semantic Web adds one more dimension to this. The workshop will
focus on the semantic web approach to personalization and
adaptation. The Web has been formed to be an integral part of
numerous applications inwhichauserinteractswithaserviceprovider,
productsellers, governmental organisations, friends and colleagues.
Content and services are available at di?erent sources and places.
Hence, Web applications need to combine all available knowledge in
order to form personalized, user-friendly, and busine- optimal
servi
In recent years, the use of Artificial Intelligence (AI) techniques
has been greatly increased. The term "intelligence" seems to be a
"must" in a large number of European and International project
calls. AI Techniques have been used in almost any domain.
Application-oriented systems usually incorporate some kind of
"intelligence" by using techniques stemming from intelligent
search, knowledge representation, machine learning, knowledge
discovery, intelligent agents, computational intelligence etc. The
Workshop on "Applications with Artificial Intelligence" seeks for
quality papers on computer applications that incorporate some kind
of AI technique. The objective of the workshop was to bring
together scientists, engineers and practitioners, who work on
designing or developing applications that use intelligent
techniques or work on intelligent techniques and apply them to
application domains (like medicine, biology, education etc), to
present and discuss their research works and exchange ideas in this
book.
Text mining is an exciting application ?eld and an area of
scienti?c - search that is currently under rapid development. It
uses techniques from well-established scienti?c ?elds (e. g. data
mining, machine learning, infor- tion retrieval, natural language
processing, case-based reasoning, statistics and knowledge
management) in an e?ort to help people gain insight, und- stand and
interpret large quantities of (usually) semi-structured and unstr-
tured data. Despite the advances made during the last few years,
many issues remain unresolved. Proper co-ordination activities,
dissemination of current trends and standardisation of the
procedures have been identi?ed, as key needs. There are many
questions still unanswered, especially to the potential users; what
is the scope of Text Mining, who uses it and for what purpose, what
constitutes the leading trends in the ?eld of Text Mining -
especially in relation to IT - and whether there still remain areas
to be covered. Knowledge Mining draws upon many of the key concepts
of knowledge management, data mining and knowledge discovery,
meta-analysis and data visualization. Within the context of
scienti?c research, knowledge mining is principally concerned with
the quantitative synthesis and visualization of - search results
and ?ndings. The results of knowledge mining are increased
scienti?c understanding along with improvements in research quality
and value. Knowledge mining products can be used to highlight
research opportunities, assist with the p- sentation of "best"
scienti?c evidence, facilitate research portfolio mana- ment, as
well as, facilitate policy setting and decision making.
Web Personalization can be de?ned as any set of actions that can
tailor the Webexperiencetoaparticularuserorsetofusers.
Toachievee?ectivepers- alization,
organizationsmustrelyonallavailabledata, includingtheusageand
click-stream data (re?ecting user behaviour), the site content, the
site str- ture, domainknowledge,
aswellasuserdemographicsandpro?les. Inaddition, e?cient and
intelligent techniques are needed to mine this data for actionable
knowledge, and to e?ectively use the discovered knowledge to
enhance the users' Web experience. These techniques must address
important challenges emanating from the size and the heterogeneous
nature of the data itself, as
wellasthedynamicnatureofuserinteractionswiththeWeb. Thesechallenges
include the scalability of the personalization solutions, data
integration, and successful integration of techniques from machine
learning, information - trievaland?ltering, databases,
agentarchitectures, knowledgerepresentation, data mining, text
mining, statistics, user modelling and human-computer - teraction.
The Semantic Web adds one more dimension to this. The workshop will
focus on the semantic web approach to personalization and
adaptation. The Web has been formed to be an integral part of
numerous applications inwhichauserinteractswithaserviceprovider,
productsellers, governmental organisations, friends and colleagues.
Content and services are available at di?erent sources and places.
Hence, Web applications need to combine all available knowledge in
order to form personalized, user-friendly, and busine- optimal
servi
In recent years, the use of Artificial Intelligence (AI) techniques
has been greatly increased. The term "intelligence" seems to be a
"must" in a large number of European and International project
calls. AI Techniques have been used in almost any domain.
Application-oriented systems usually incorporate some kind of
"intelligence" by using techniques stemming from intelligent
search, knowledge representation, machine learning, knowledge
discovery, intelligent agents, computational intelligence etc. The
Workshop on "Applications with Artificial Intelligence" seeks for
quality papers on computer applications that incorporate some kind
of AI technique. The objective of the workshop was to bring
together scientists, engineers and practitioners, who work on
designing or developing applications that use intelligent
techniques or work on intelligent techniques and apply them to
application domains (like medicine, biology, education etc), to
present and discuss their research works and exchange ideas in this
book.
The world of text mining is simultaneously a minefield and a gold
mine. It is an exciting application field and an area of scientific
research that is currently under rapid development. It uses
techniques from well-established scientific fields (e.g. data
mining, machine learning, information retrieval, natural language
processing, case based reasoning, statistics and knowledge
management) in an effort to help people gain insight, understand
and interpret large quantities of (usually) semi-structured and
unstructured data. Despite the advances made during the last few
years, many issues remain umesolved. Proper co-ordination
activities, dissemination of current trends and standardisation of
the procedures have been identified, as key needs. There are many
questions still unanswered, especially to the potential users; what
is the scope of Text Mining, who uses it and for what purpose, what
constitutes the leading trends in the field of Text Mining
-especially in relation to IT- and whether there still remain areas
to be covered."
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