Rapid Prototyping of a Semantic-Web-based Research Workbench

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Carsten Ullrich

Talk at the UDS-SJTU Joint Research Lab for Language Technology. I describe I project I did for Totuba.

Technology Education

Rapid Prototyping of a
Semantic-Web-based
Research Workbench

Carsten Ullrich
Dept. of Computer Science and
Engineering, SJTU

Overview
• Project done with Totuba, Inc.
• Goal: develop a research workbench
– bibliography manager
– research network
– support while writing research papers
• Sorry, no new pure research results
• But: overview on state-of-the-art of
existing Web services / Web data

• context-sensitive further
reading
• related topics
• drag&drop referencing

Entity Extraction
The term "Web 2.0" is used to describe applications that
distinguish themselves from previous generations of software by
a number of principles. Existing work shows that Web 2.0
applications can be successfully exploited for technology-
enhanced learning. However, in-depth analyses of the
relationship between Web 2.0 technology on the one hand and
teaching and learning on the other hand are still rare.

Entity Extraction
Gur grez "Jro 2.0" vf hfrq gb qrfpevor nccyvpngvbaf gung
qvfgvathvfu gurzfryirf sebz cerivbhf trarengvbaf bs fbsgjner ol n
ahzore bs cevapvcyrf. Rkvfgvat jbex fubjf gung Jro 2.0
nccyvpngvbaf pna or fhpprffshyyl rkcybvgrq sbe grpuabybtl-
raunaprq yrneavat. Ubjrire, va-qrcgu nanylfrf bs gur
eryngvbafuvc orgjrra Jro 2.0 grpuabybtl ba gur bar unaq naq
grnpuvat naq yrneavat ba gur bgure unaq ner fgvyy ener.

Open Calais
• Thomson Reuters company
• Web Service
• Extracts entities, facts,
events (about 100 types)
• Free for noncommercial and
commercial use

Entities
Anniversary, City, Company, Continent, Country, Currency, EmailAddress,
EntertainmentAwardEvent, Facility, FaxNumber, Holiday, IndustryTerm, MarketIndex,
MedicalCondition, MedicalTreatment, Movie, MusicAlbum, MusicGroup, NaturalFeature,
OperatingSystem, Organization, Person, PhoneNumber, Position, Product, ProgrammingLanguage,
ProvinceOrState, PublishedMedium, RadioProgram, RadioStation, Region, SportsEvent,
SportsGame, SportsLeague, Technology, TVShow, TVStation, URL

Semantifying
The term "Web 2.0“...

OpenCalais
• Web 2.0
• technology-supported learning

DBPedia (others: Yago, Freebase, UMBEL)

• http://dbpedia.org/resource/Web_2.0
• http://dbpedia.org/resource/Technology-Enhanced_Learning

Related Topics: Web_2.0 in DBPedia

• skos:subject
– dbpedia:Category:Buzzwords
– dbpedia:Category:Branding
– dbpedia:Category:Cloud_applications
– dbpedia:Category:Internet_memes
– dbpedia:Category:Social_Information_Processing
– dbpedia:Category:World_Wide_Web
– dbpedia:Category:Web_2.0
– dbpedia:Category:Web_services

Reuse
• Highly efficient entity extraction
• Enormous databases
– describe the entities
– link to related entities

• Give a high-level starting position to explore new
challenges
– how to put this data into use?
– context: what is relevant for user/current usage

Lessons Learned
• Reuse enables progress
– no duplication of work
– focus on problems relevant for you
• Having a landscape that encourages reuse
creates advantages for research / commercial
applications
• Problems
– mostly only English
– few Chinese services / programming libraries
• e.g., named entity extraction

Questions
• I have some:
– opinion mining
– information extraction

Questions
• I have some:
– opinion mining
– information extraction

• Any toolkits available? RASCALLI?
• Contact me in case you find this
interesting
• ullrich_c@sjtu.edu.cn

This work analyses the problem coming from the so called Big Data scenario, which can be defined as the technological challenge to manage and administer quantity of information with global dimension in the order of Terabyte (〖10〗^12 bytes) or Petabyte (〖10〗^15 bytes) and with an exponential growth rate. We’ll explore a technological and algorithmic approach to handle and calculate theses amounts of data that exceed the limit of computation of a traditional architecture based on real-time request processing: in particular we’ll analyze a singular open source technology, called Apache Hadoop, which implements the approach described as Map and Reduce. We’ll describe also how to distribute a cluster of common server to create a Virtual File System and use this environment to populate a centralized search index (realized using another open source technology, called Apache Lucene). The practical implementation will be a web based application which offers to the user a unified searching interface against a collection of technical papers. The scope is to demonstrate that a performant search system can be obtained pre-processing the data using the Map and Reduce paradigm, in order to obtain a real time response, which is independent to the underlying amount of data. Finally we’ll compare this solutions to different approaches based on clusterization or No SQL solutions, with the scope to describe the characteristics of concrete scenarios, which suggest the adoption of those technologies.

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ALTER WAY

Elasticsearch est un moteur de recherche Open Source très puissant basé sur Apache Lucene. Il permet l'indexation de millions de données, leur recherche et leur analyse en temps réel. Les outils Elascticsearch sont déjà utilisés par des acteurs de référence tels que FourSquare, GitHub, OpenDataSoft ou encore Dailymotion. Alter Way et Elasticsearch vous convient à venir découvrir la suite Elasticsearch enfin disponible en version 1.0 et prête pour la production !

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Useful unstructured text occurs in plentiful amounts, and often is central to the success of a business. The benefits of being able to successfully decipher unstructured text can be direct or derived. Companies which offer products for medical differential diagnosis are directly benefitted by the ability to correctly extract drug-disease interactions from publications, for example. As for derived benefits of text processing, we need to look no further than cases of improving process flows by analyzing the sentiment of the emails a company receives from its customers. Being at the frontier of natural language processing, information representation and retrieval, information extraction has been the subject of extensive research for several decades and there are plenty of existing techniques to help with the understanding of unstructured textual content. This presentation will introduce and summarize useful techniques that are helpful in tackling sub-domains of information extraction, such as named entity recognition, keyword extraction and document summarization for efficient retrieval. Additionally, the talk will also emphasize low-resource cases, when not much useful labelled information is available.

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An ontology expresses a common understanding of a domain that serves as a basis of communication between people or systems, and enables knowledge sharing, reuse of domain knowledge, reasoning and thus problem solving. In Technology-Enhanced Learning, especially in Intelligent Tutoring Systems and Adaptive Learning Environments, ontologies serve as the basis of adaptivity and personalization. For mathematics learning and similarly structured domains, ontologies and their usage for adaptive learning are well understood and established. This contribution presents an ontology for the industrial shop floor (the area of a factory where operatives assemble products) and illustrates its usage in several learning services.

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Rapid Prototyping of a Semantic-Web-based Research Workbench

1. Rapid Prototyping of a Semantic-Web-based Research Workbench Carsten Ullrich Dept. of Computer Science and Engineering, SJTU

2. Overview • Project done with Totuba, Inc. • Goal: develop a research workbench – bibliography manager – research network – support while writing research papers • Sorry, no new pure research results • But: overview on state-of-the-art of existing Web services / Web data

3. • context-sensitive further reading • related topics • drag&drop referencing

4. Entity Extraction The term "Web 2.0" is used to describe applications that distinguish themselves from previous generations of software by a number of principles. Existing work shows that Web 2.0 applications can be successfully exploited for technology- enhanced learning. However, in-depth analyses of the relationship between Web 2.0 technology on the one hand and teaching and learning on the other hand are still rare.

5. Entity Extraction Gur grez "Jro 2.0" vf hfrq gb qrfpevor nccyvpngvbaf gung qvfgvathvfu gurzfryirf sebz cerivbhf trarengvbaf bs fbsgjner ol n ahzore bs cevapvcyrf. Rkvfgvat jbex fubjf gung Jro 2.0 nccyvpngvbaf pna or fhpprffshyyl rkcybvgrq sbe grpuabybtl- raunaprq yrneavat. Ubjrire, va-qrcgu nanylfrf bs gur eryngvbafuvc orgjrra Jro 2.0 grpuabybtl ba gur bar unaq naq grnpuvat naq yrneavat ba gur bgure unaq ner fgvyy ener.

6. Entity Extraction Gur grez "Jro 2.0" vf hfrq gb qrfpevor nccyvpngvbaf gung qvfgvathvfu gurzfryirf sebz cerivbhf trarengvbaf bs fbsgjner ol n ahzore bs cevapvcyrf. Rkvfgvat jbex fubjf gung Jro 2.0 nccyvpngvbaf pna or fhpprffshyyl rkcybvgrq sbe grpuabybtl- raunaprq yrneavat. Ubjrire, va-qrcgu nanylfrf bs gur eryngvbafuvc orgjrra Jro 2.0 grpuabybtl ba gur bar unaq naq grnpuvat naq yrneavat ba gur bgure unaq ner fgvyy ener. OpenCalais • Jro 2.0 • grpuabybtl-raunaprq yrneavat

7. Open Calais • Thomson Reuters company • Web Service • Extracts entities, facts, events (about 100 types) • Free for noncommercial and commercial use Entities Anniversary, City, Company, Continent, Country, Currency, EmailAddress, EntertainmentAwardEvent, Facility, FaxNumber, Holiday, IndustryTerm, MarketIndex, MedicalCondition, MedicalTreatment, Movie, MusicAlbum, MusicGroup, NaturalFeature, OperatingSystem, Organization, Person, PhoneNumber, Position, Product, ProgrammingLanguage, ProvinceOrState, PublishedMedium, RadioProgram, RadioStation, Region, SportsEvent, SportsGame, SportsLeague, Technology, TVShow, TVStation, URL

8. Semantifying The term "Web 2.0“... OpenCalais • Web 2.0 • technology-supported learning DBPedia (others: Yago, Freebase, UMBEL) • http://dbpedia.org/resource/Web_2.0 • http://dbpedia.org/resource/Technology-Enhanced_Learning

9. Related Topics: Web_2.0 in DBPedia • skos:subject – dbpedia:Category:Buzzwords – dbpedia:Category:Branding – dbpedia:Category:Cloud_applications – dbpedia:Category:Internet_memes – dbpedia:Category:Social_Information_Processing – dbpedia:Category:World_Wide_Web – dbpedia:Category:Web_2.0 – dbpedia:Category:Web_services

10. Linked Open Data dataset cloud

11. Reuse • Highly efficient entity extraction • Enormous databases – describe the entities – link to related entities • Give a high-level starting position to explore new challenges – how to put this data into use? – context: what is relevant for user/current usage

12. Lessons Learned • Reuse enables progress – no duplication of work – focus on problems relevant for you • Having a landscape that encourages reuse creates advantages for research / commercial applications • Problems – mostly only English – few Chinese services / programming libraries • e.g., named entity extraction

13. Questions • I have some: – opinion mining – information extraction

14.

15.

16. Questions • I have some: – opinion mining – information extraction • Any toolkits available? RASCALLI? • Contact me in case you find this interesting • ullrich_c@sjtu.edu.cn

Rapid Prototyping of a Semantic-Web-based Research Workbench

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