This paper was presented at the Fifth International Workshop on Resource Discovery (RED 2012: http://www.labf.usb.ve/RED2012/) at ESWC 2012 (http://2012.eswc-conferences.org/) Conference in Heraklion, Crete, Greece on 27 May 2012.
The full paper can be found at: http://ceur-ws.org/Vol-862/REDp5.pdf
These slides explain (1) the motivation for using RDFa, for embedding structured data on web pages, (2) RDF as the foundation of RDFa, and (3) RDFa through examples.
Intelligent Expert systems can provide decisions for users for estimate from user preferences to find better destination from user profits. this present provides description of above system and suggest new approach for next researches.
Semantic Massage Addressing based on Social Cloud Actor's InterestsCSCJournals
Wireless communication with Mobile Terminals has become popular tools for collecting and sending information and data. With mobile communication comes the Short Message Service (SMS) technology which is an ideal way to stay connected with anyone, anywhere anytime to help maintain business relationships with customers. Sending individual SMS messages to long list of mobile numbers can be very time consuming, and face problems of wireless communications such as variable and asymmetric bandwidth, geographical mobility and high usage costs and face the rigidity of lists. This paper proposes a technique that assures sending the message to semantically specified group of recipients. A recipient group is automatically identified based on personal information (interests, work place, publications, social relationships, etc.) and behavior based on a populated ontology created by integrating the publicly available FOAF (Friend-of-a-Friend) documents. We demonstrate that our simple technique can first, ensure extracting groups effectively according to the descriptive attributes and second send SMS effectively and can help combat unintentional spam and preserve the privacy of mobile numbers and even individual identities. The technique provides fast, effective, and dynamic solution to save time in constructing lists and sending group messages which can be applied both on personal level or in business.
This tutorial, offered at the 10th International Conference on Web Engineering, presents the peculiarities of advanced Web search applications, describes some tools and techniques that can be exploited, and offers a methodological approach to development. The approach proposed in this tutorial is based on the paradigm of Model Driven Development (MDD), where models are the core artifacts of the application life-cycle and model transformations progressively refine models to achieve an executable version of the system. To cope with the process-intensive nature of the main interactions (i.e., content analysis, query management, etc.), we describe the use of Process Models (e.g., BPMN models). Indeed, search-based applications are considered as process- and content-intensive applications, due to the trends towards exploratory search and search as a process visions.
These slides explain (1) the motivation for using RDFa, for embedding structured data on web pages, (2) RDF as the foundation of RDFa, and (3) RDFa through examples.
Intelligent Expert systems can provide decisions for users for estimate from user preferences to find better destination from user profits. this present provides description of above system and suggest new approach for next researches.
Semantic Massage Addressing based on Social Cloud Actor's InterestsCSCJournals
Wireless communication with Mobile Terminals has become popular tools for collecting and sending information and data. With mobile communication comes the Short Message Service (SMS) technology which is an ideal way to stay connected with anyone, anywhere anytime to help maintain business relationships with customers. Sending individual SMS messages to long list of mobile numbers can be very time consuming, and face problems of wireless communications such as variable and asymmetric bandwidth, geographical mobility and high usage costs and face the rigidity of lists. This paper proposes a technique that assures sending the message to semantically specified group of recipients. A recipient group is automatically identified based on personal information (interests, work place, publications, social relationships, etc.) and behavior based on a populated ontology created by integrating the publicly available FOAF (Friend-of-a-Friend) documents. We demonstrate that our simple technique can first, ensure extracting groups effectively according to the descriptive attributes and second send SMS effectively and can help combat unintentional spam and preserve the privacy of mobile numbers and even individual identities. The technique provides fast, effective, and dynamic solution to save time in constructing lists and sending group messages which can be applied both on personal level or in business.
This tutorial, offered at the 10th International Conference on Web Engineering, presents the peculiarities of advanced Web search applications, describes some tools and techniques that can be exploited, and offers a methodological approach to development. The approach proposed in this tutorial is based on the paradigm of Model Driven Development (MDD), where models are the core artifacts of the application life-cycle and model transformations progressively refine models to achieve an executable version of the system. To cope with the process-intensive nature of the main interactions (i.e., content analysis, query management, etc.), we describe the use of Process Models (e.g., BPMN models). Indeed, search-based applications are considered as process- and content-intensive applications, due to the trends towards exploratory search and search as a process visions.
SharePoint’s rapid adoption is undeniable but it raises one important question: What security capabilities did Microsoft implement to ensure that SharePoint--and the data it houses--remains secure? SharePoint’s functionality was built for business users to share information. However, business users don’t typically recognize critical security considerations. This leaves security teams with the task of layering security onto SharePoint well after deployments, or worse, after a data breach. These presentation slides highlight SharePoint use cases and potential security issues , offer best practices for SharePoint security planning and management, and provide key mitigation steps that enterprises implement to minimize the odds of a data breach.
Linked data for Enterprise Data IntegrationSören Auer
The Web evolves into a Web of Data. In parallel Intranets of large companies will evolve into Data Intranets based on the Linked Data principles. Linked Data has the potential to complement the SOA paradigm with a light-weight, adaptive data integration approach.
Phishing Attacks: Trends, Detection Systems and Computer Vision as a Promisin...Selman Bozkır
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In present times any marketing or customer strategy is incomplete without a social media presence. With customers depending all the more on social media channels to access and disseminate information and reviews, it becomes all the more important for organizations to tap social media channels for actionable insights.
An Ontology-based Technique for Online Profile Resolutionkcortis
This paper was presented at the 5th International Conference on Social Informatics (http://www.socinfo2013.com/) in Kyoto, Japan on 27 November 2013.
The full paper can be found at: http://link.springer.com/chapter/10.1007%2F978-3-319-03260-3_25
An introduction to Facebook Graph API and OAuth 2. This presentation covers basic example of Facebook Graph API, and including how OAuth 2 client-side flow works.
Sentiment analysis using naive bayes classifier Dev Sahu
This ppt contains a small description of naive bayes classifier algorithm. It is a machine learning approach for detection of sentiment and text classification.
SharePoint’s rapid adoption is undeniable but it raises one important question: What security capabilities did Microsoft implement to ensure that SharePoint--and the data it houses--remains secure? SharePoint’s functionality was built for business users to share information. However, business users don’t typically recognize critical security considerations. This leaves security teams with the task of layering security onto SharePoint well after deployments, or worse, after a data breach. These presentation slides highlight SharePoint use cases and potential security issues , offer best practices for SharePoint security planning and management, and provide key mitigation steps that enterprises implement to minimize the odds of a data breach.
Linked data for Enterprise Data IntegrationSören Auer
The Web evolves into a Web of Data. In parallel Intranets of large companies will evolve into Data Intranets based on the Linked Data principles. Linked Data has the potential to complement the SOA paradigm with a light-weight, adaptive data integration approach.
Phishing Attacks: Trends, Detection Systems and Computer Vision as a Promisin...Selman Bozkır
In this presentation, I first introduce the problem of phishing covering the following issues: (a) statistics reported by APWG, (b) the types of phishing attacks, and (c) example phishing e-mails. Next, I discuss why this problem has not yet been solved. Later, after having demonstrated several studies, I state various reasons why and how computer vision can help us to combat phishing. Finally, I present our futuristic vision towards new generation phishing detection systems employing deep neural network-based image recognition and segmentation schemes
Digital Object Identifier (DOI): Introduction and Applications Nader Ale Ebrahim
The Digital Object Identifier (DOI) is used for identifying intellectual property in the digital environment. The DOI is like a digital fingerprint: Each article receives a unique one at birth, and it can be used to identify the article throughout its lifespan, no matter where it goes. A DOI should be interpreted as 'digital identifier of an object' rather than 'identifier of a digital object'. A DOI can be assigned to any Object. In this workshop you will learn how to define a DOI, prepare Meta Data, and assign a DOI for a journal paper.
In present times any marketing or customer strategy is incomplete without a social media presence. With customers depending all the more on social media channels to access and disseminate information and reviews, it becomes all the more important for organizations to tap social media channels for actionable insights.
An Ontology-based Technique for Online Profile Resolutionkcortis
This paper was presented at the 5th International Conference on Social Informatics (http://www.socinfo2013.com/) in Kyoto, Japan on 27 November 2013.
The full paper can be found at: http://link.springer.com/chapter/10.1007%2F978-3-319-03260-3_25
An introduction to Facebook Graph API and OAuth 2. This presentation covers basic example of Facebook Graph API, and including how OAuth 2 client-side flow works.
Sentiment analysis using naive bayes classifier Dev Sahu
This ppt contains a small description of naive bayes classifier algorithm. It is a machine learning approach for detection of sentiment and text classification.
Querying Heterogeneous Datasets on the Linked Data WebEdward Curry
The growing number of datasets published on the Web as linked data brings both opportunities for high data availability and challenges inherent to querying data in a semantically heterogeneous and distributed environment. Approaches used for querying siloed databases fail at Web-scale because users don't have an a priori understanding of all the available datasets. This article investigates the main challenges in constructing a query and search solution for linked data and analyzes existing approaches and trends.
February 18 2015 NISO Virtual Conference
Scientific Data Management: Caring for Your Institution and its Intellectual Wealth
Network Effects: RMap Project
Sheila M. Morrissey, Senior Researcher, ITHAKA
Digital Renaissance - Alfresco EMEA Partner DayJohn Newton
The Digital Renaissance is the convergence of the forces of Cloud, Mobile, Big Data and Social affecting the way that all industries do business. A virtuous cycle of customer engagement and business agility drive the redesign of business models and they way we all work together. New technologies and architectures are required to participate in the biggest changes to affect business since who knows when.
Self-Sovereign Identity technology has enormous potential to empower individuals and address privacy challenges globally. It uses shared ledgers (blockchain) to give individuals the power to create and manage their own identifiers, collect verified claims and interact with others on the network on their terms. This lighting talk by one of the pioneers working on this new emerging layer of the internet for 15 years will give a high level picture of how it works covering the core standards and technologies along with outlining some potential use-cases.
Presentation on an overview of LinkedIn data driven products and infrastructure given on 26 Oct 2012 in the big-data symposium given in honor of the retirement of my PhD advisor Dr Martin H. Schultz.
A distributional structured semantic space for querying rdf graph dataAndre Freitas
The vision of creating a Linked Data Web brings together the challenge of allowing queries across highly heterogeneous and distributed datasets. In order to query Linked Data on the Web today, end users need to be aware of which datasets potentially contain the data and also which data model describes these datasets. The process of allowing users to expressively query relationships in RDF while abstracting them from the underlying data model represents a fundamental problem for Web-scale Linked Data consumption. This article introduces a distributional structured semantic space which enables data model independent natural language queries over RDF data. The center of the approach relies on the use of a distributional semantic model to address the level of semantic interpretation demanded to build the data model independent approach. The article analyzes the geometric aspects of the proposed space, providing its description as a distributional structured vector space, which is built upon the Generalized Vector Space Model (GVSM). The final semantic space proved to be flexible and precise under real-world query conditions achieving mean reciprocal rank = 0.516, avg. precision = 0.482 and avg. recall = 0.491.
Us, Our Organizations and the Evolving Web: Leveraging Identity Tools for Collaboration. This talk was given at the Net Squared 2008 Conference. The goal was to share some of the activity ongoing in the identity community, how it might be used by the nonprofit sector and invite their involvement in its continued development.
Welocme to ViralQR, your best QR code generator.ViralQR
Welcome to ViralQR, your best QR code generator available on the market!
At ViralQR, we design static and dynamic QR codes. Our mission is to make business operations easier and customer engagement more powerful through the use of QR technology. Be it a small-scale business or a huge enterprise, our easy-to-use platform provides multiple choices that can be tailored according to your company's branding and marketing strategies.
Our Vision
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Our Achievements
Ever since its inception, we have successfully served many clients by offering QR codes in their marketing, service delivery, and collection of feedback across various industries. Our platform has been recognized for its ease of use and amazing features, which helped a business to make QR codes.
Our Services
At ViralQR, here is a comprehensive suite of services that caters to your very needs:
Static QR Codes: Create free static QR codes. These QR codes are able to store significant information such as URLs, vCards, plain text, emails and SMS, Wi-Fi credentials, and Bitcoin addresses.
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Pricing and Packages
Additionally, there is a 14-day free offer to ViralQR, which is an exceptional opportunity for new users to take a feel of this platform. One can easily subscribe from there and experience the full dynamic of using QR codes. The subscription plans are not only meant for business; they are priced very flexibly so that literally every business could afford to benefit from our service.
Why choose us?
ViralQR will provide services for marketing, advertising, catering, retail, and the like. The QR codes can be posted on fliers, packaging, merchandise, and banners, as well as to substitute for cash and cards in a restaurant or coffee shop. With QR codes integrated into your business, improve customer engagement and streamline operations.
Comprehensive Analytics
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So, thank you for choosing ViralQR; we have an offer of nothing but the best in terms of QR code services to meet business diversity!
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
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The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
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Gopinath Rebala
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Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
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Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
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Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
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Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
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Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
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Assure Contact Center Experiences for Your Customers With ThousandEyes
Discovering Semantic Equivalence of People behind Online Profiles (RED 2012 - ESWC 2012)
1. Digital Enterprise Research Institute
www.deri.ie
Discovering Semantic Equivalence
of People behind
Online Profiles
Keith Cortis, Simon Scerri, Ismael Rivera, Siegfried
Handschuh
REsource Discovery (RED),
Workshop at ESWC 2012
27th May 2012
Copyright 2011 Digital Enterprise Research Institute. All rights reserved.
Enabling Networked Knowledge
2. Motivation
Digital Enterprise Research Institute
www.deri.ie
Current situation:
Personal data is
unnecessarily duplicated
over different platforms
No possibility to merge or
port such data
Separate handling of this
data
Social Networking Sites as Walled
Gardens – David Simonds
Enabling Networked Knowledge
3. Problem Specification
Digital Enterprise Research Institute
www.deri.ie
No common standards exist for modelling profile data in
online accounts
Personal data (known contacts and presence
information) is dynamic and continuously changing
Enabling Networked Knowledge
4. Objectives
Digital Enterprise Research Institute
www.deri.ie
Aim: User represented through one digital identity
Main Challenge: Discovery of semantic equivalence
between contacts described in online profiles
Proposal: Use a comprehensive ontology framework for
handling online profile data
Enabling Networked Knowledge
6. Related Work Comparison
Digital Enterprise Research Institute
www.deri.ie
Existing Profile Linking Approaches based on:
o
o
Specific Inverse Functional Properties (e.g. email address)
o
Syntactic matching of all profile attributes
o
User’s friends
Semantic relatedness between text, depending on Knowledge
Bases (KB) such as Wikipedia
Our Approach: Similarity measure based on user’s
Personal Information Model (PIM)
PIM
Enabling Networked Knowledge
7. Approach (1)
Digital Enterprise Research Institute
www.deri.ie
A
User Profile Data
B
Ontology Mapping
C
Matching Attributes
D
Value Matching
Indirect String Matching
Linguistic
Analysis
2
Syntactic Matching
Direct String Matching
1
3
4
Semantic
Search
Extension
Ontologyenhanced
Attribute
Weighting
Online Profile Resolution
Enabling Networked Knowledge
8. Approach (2)
Digital Enterprise Research Institute
www.deri.ie
A
User Profile Data
B
Ontology Mapping
C
Matching Attributes
D
Value Matching
Indirect String Matching
Linguistic
Analysis
2
Syntactic Matching
Direct String Matching
1
3
4
Semantic
Search
Extension
Ontologyenhanced
Attribute
Weighting
Online Profile Resolution
Enabling Networked Knowledge
9. Approach (3)
Digital Enterprise Research Institute
www.deri.ie
A
User Profile Data
B
Ontology Mapping
C
Matching Attributes
D
Value Matching
Indirect String Matching
Linguistic
Analysis
2
Syntactic Matching
Direct String Matching
1
3
4
Semantic
Search
Extension
Ontologyenhanced
Attribute
Weighting
Online Profile Resolution
Enabling Networked Knowledge
10. Approach (3)
Digital Enterprise Research Institute
www.deri.ie
Identity-related online profile information - NCO
Presence and online post data for the user – DLPO
Enabling Networked Knowledge
11. Approach (3)
Digital Enterprise Research Institute
www.deri.ie
Account Ontology (DAO) – for modelling service account
representations
DLPO
representative
Contact
DAO
LivePost
MultimediaPost
PresencePost
WebDocumentPost
Message
Account
source
source
hasCredentials
Credentials
nao:externalIdentifier
rdfs:label
rdfs:label
userID
password
xsd:string
hasCustomAttribute
NCO
PersonContact
photo
key
sound
foafUrl
OrganizationContact
rdfs:Resource websiteUrl
blogUrl
nie:DataObject
EmailAddress hasEmailAddressbelongsToGroup
ContactGroup
PostalAddress hasPostalAddress
PhoneNumber hasPhoneNumber hasLocation
geo:Point
hasIMAccount
Name
IMAccount
hasName
Enabling Networked Knowledge
12. Approach (4)
Digital Enterprise Research Institute
www.deri.ie
A
User Profile Data
B
Ontology Mapping
C
Matching Attributes
D
Value Matching
Indirect String Matching
Linguistic
Analysis
2
Syntactic Matching
Direct String Matching
1
3
4
Semantic
Search
Extension
Ontologyenhanced
Attribute
Weighting
Online Profile Resolution
Enabling Networked Knowledge
13. Approach (4)
Digital Enterprise Research Institute
www.deri.ie
A
User Profile Data
B
Ontology Mapping
C
Matching Attributes
D
Value Matching
Indirect String Matching
Linguistic
Analysis
2
Syntactic Matching
Direct String Matching
1
3
4
Semantic
Search
Extension
Ontologyenhanced
Attribute
Weighting
Online Profile Resolution
Enabling Networked Knowledge
14. Approach (4)
Digital Enterprise Research Institute
www.deri.ie
A
User Profile Data
B
Ontology Mapping
C
Matching Attributes
D
Value Matching
Indirect String Matching
Linguistic
Analysis
2
Syntactic Matching
Direct String Matching
1
3
4
Semantic
Search
Extension
Ontologyenhanced
Attribute
Weighting
Online Profile Resolution
Enabling Networked Knowledge
15. Approach (4)
Digital Enterprise Research Institute
www.deri.ie
A
User Profile Data
B
Ontology Mapping
C
Matching Attributes
D
Value Matching
Indirect String Matching
Linguistic
Analysis
2
Syntactic Matching
Direct String Matching
1
3
4
Semantic
Search
Extension
Ontologyenhanced
Attribute
Weighting
Online Profile Resolution
Enabling Networked Knowledge
16. Approach (4)
Digital Enterprise Research Institute
www.deri.ie
A
User Profile Data
B
Ontology Mapping
C
Matching Attributes
D
Value Matching
Indirect String Matching
Linguistic
Analysis
2
Syntactic Matching
Direct String Matching
1
3
4
Semantic
Search
Extension
Ontologyenhanced
Attribute
Weighting
Online Profile Resolution
Enabling Networked Knowledge
17. Approach (5)
Digital Enterprise Research Institute
www.deri.ie
A
User Profile Data
B
Ontology Mapping
C
Matching Attributes
D
Value Matching
Indirect String Matching
Linguistic
Analysis
2
Syntactic Matching
Direct String Matching
1
3
4
Semantic
Search
Extension
Ontologyenhanced
Attribute
Weighting
Online Profile Resolution
Enabling Networked Knowledge
18. Implementation
Digital Enterprise Research Institute
www.deri.ie
Transformation
Linguistic Analysis
ANNIE
Information
Extraction System
Large KB
Gazetteer
Lookup
“DERI, Lower Dangan, Galway, Ireland”
PIM
Organisation
Street
City
Country
Enabling Networked Knowledge
20. Summary
Digital Enterprise Research Institute
www.deri.ie
Objectives
o
o
Future Work
Aggregated profile data is
lifted onto a unique PIM
representation and
integrated in a super profile
o
Integration of further online
accounts
o
Semantic extension to the
syntactic-based profile
attribute matching
o
Definition of a metric
o
Analysis of online posts
from multiple accounts
o
Determination of semantic
equivalence between
contacts described in online
profiles
Evaluation of artefact
Thank you for your attention
keith.cortis@deri.org
Enabling Networked Knowledge
Editor's Notes
-Users are currently required to create and separately manage duplicated personal data in numerous, heterogeneous online account services-Walled Garden: separate handling of data results in creating a wall around connections and personal data as reflected in the image -> portability, identity, linkability, privacy-Personal data In these accounts: static identity-related information to more dynamic information, as well as physical and online presence.
-Focus of study not a straightforward task:1. no common standards exist for modelling profile data in online accounts -> retrieval and integration of federated heterogeneous personal data is instantly a hard task 2. some personal data is dynamic (known contacts and presence information) -> Dealing with the multiple user digital identities can result in being a complex task
Aim: enable user to create, aggregate and merge multiple online profiles in one digital identity -One digital identity through Digital.Meuserware: i)a single access point to the user’s personal information sphere, ii) refers to personal data on a user’s multiple devices such as laptops, tablets and smartphones (after challenge) – online profile, their attributes and shared posts.Focus: Integration of multiple user online profiles - (e.g. health, bank, government, social related) but currently our focus is on social networksProposal: This comes in the form of a comprehensive ontology framework, which serves as a standard format for handling static and dynamic profile data (a set of re-used, extended and new vocabularies)
Pyramid of the OSCAF Ontologies – adopted by di.meframwork (reused, extended, new) PIM representation uses these ontologies. – based on PIMO, NCO, DLPO For the problem in question (multiple identity integration), of particular relevance are the:NCO : modelling profile attributesPIMO: modelling user’s interests & who knows whom (NCO, PIMO all are established) - glues together knowledge represented by all the other domain upper-level ontologiesLivePost Ontology: modelling online posts (just 1 of a no. of new ontologies being engineered)Other targeting domains: user presence (DPO), context (DCON), history (DUHO), rules (DRMO), devices (DDO), accounts (DAO)In Di.me a no. of established ontologies have been brought together to offer a representation solution tailored for the project's objectives (reused, extended, new)
-IFP : a property which uniquely identifies a user : linking based on IFP only is shallow since users can create multiple accounts within the same social network, with a diff email-Personal Information Model - an instance of PIMO ontology : main KB for semantic matching, knowledge from external KBs-PIM: initially populated with any personal info integrated from a part. online account/crawled from a device. If there is no match of a particular entity, a new instance is created. (there will be one user profile initially)-Adv of PIM: contains info that is of direct interest to the user, thus more relevant to user than external KB – bound to yield more accurate results-remote KBs such as DPBedia or any other dataset that is part of the LOD cloud, will be accessed to determine any possible semantic relationship if no data exists in PIM
Online profile matching approach involvesfour successive processes as outlined in the image presented.
-Retrieve user’s profile information available through the service account APIs. Info targeted: user’s own identity-related information, online posts, contact’s info. - All crawled info. is aggregated into what we refer to as the user’s ‘super profile’
Mapping of attributes for each represented online profile with the equivalent attributes for the super profile -The use of ontologies and RDF (main data representation) -> mapping we pursue considers both syntactic as well as semantic similarities in between online profile data
Identity-related online profile information is stored as an instance of the NCO ontology – represents info that is related to a part contactPresence and online post data for the user is stored as instances of DLPO – represents personal presence info that is popularly shared in online accounts e.g. stat msg, checkin, etc.
Contacts (NCO instance) and Liveposts (DLPO instance) are linked to instances of accounts (dao:Account), that refer to a particular account e.g. di.me, LinkedIn, Facebook, Twitter
-Matching the user profile attributes - we consider the data both at a semantic and syntactic level. It involves four successive processes as outlined in (C)
1. Linguistic Analysis: - on the profile attributes that may contain complex/unstructured information such as a postal address, unlike the ones with an atomic value (person’s name, phone number). Required for discovering further knowledge from a particular value. Also, hyperlink resolution if not enough info within profile.
2. Syntactic Matching: -Value Matching: for attr. of a non-string literal type (e.g. dob or geo pos), since these have a strict, predefined structure -Direct String Matching: for attr. of type ‘string’, if their ontology type (e.g. name, addr) is either known beforehand or discovered through NER -Indirect String Matching: applied if attr. entity remains unknown even after NER is performed, over all PIM instances, regardless of their type -string matching metric – Monge and Elkan: user profile attribute values online to attributes stored in PIM KB
3. Semantic Search Extension: -To find if 2 attributes are semantically related, given that they don’t syntactically match. -user’s PIM is the main KB used, whilst remote KBs e.g. DBPedia or any other dataset in LOD cloud will also be used to determine any possible semantic relationship, if required data not found within the PIM.
4. Ontology-enhanced Attribute Weighting: an appropriate metric is required for weighting the attributes which were syntactically and/or semantically matched
-Based on the ontology attribute weighting metric, we establish a threshold which determines semantic equivalence between user online profile and their personal identity which is already known and represented at the PIM level.-Given that 2 profiles are sem. eq., a user can be suggested to merge profile info that’s known over multiple online accounts-Integration of semantically-equivalent personal info across distributed sources will create unique user representation in the PIM
XSPARQL - transformation between the XML social data into our RDF representation (Turtle) is declaratively expressed in a XSPARQL queryJSONLib– used to translate JSON into XMLANNIE – contains several main processing resources for common NLP tasks, such as a: tokeniser, sentence splitter, POS tagger, gazetteer, finite state transducer, orthomatcher and coreference resolver -> pre-defined gazetteers for common entity types (e.g. location, organizations, etc.), which we extended with acr. or abbr. where necessaryLarge KB Gazetteer - to make use of the information stored within the user’s PIM, since it can get populated dynamically by loading any ontology from RDF data.
-User’s Personal Information Model (PIM) - glues together personal info from different sources in this case:-from an online account (OnlineAccountX) & the user’s super profile (Digital.MeAccount)-attributes of the user online profiles will be mapped to their corresponding properties within the di.me ontology framework-five identity-related profile attributes mapped within NCO (affiliation, organization, phone numer, person name, postal address) -e.g. label of org within the nco:org property i.e. ’Digital Enterprise Research Institute’ is matched against other org instances within the PIM The super profile instance ’DERI’ is one example of other PIM instances having the same type.-Presence-related profile info. available in the form of a complex type ’livepost’, is composed of… - ”Having a beer with Anna @ESWC12 in Iraklion” -> Status & Checkin & Event Post -> result of Linguistic analysis on online post -Semantic search example:-user’s addr in super profile listed as ‘Iraklion, is related to a pimo:City instance – ‘Heraklion’-user’s addr in online profile is ‘GR’, is related to pimo:Country instance –’Greece.’-two addr’s don’t syntactically match but are semantically related-through PIM KB, system knows that city and country instances related to both addr’s are related through ‘locatedWithin’ property -> partial semantic searchAdv of using ontologies: - resources can be linked at the semantic level, rather than the syntactic or format level.pimo:groundingOccurrence property, which relates an ’abstract’ but unique subject to one or more of its occurrences.-upper part of Fig. T-Box -> the ontological classes and attributes / lower part of Fig. A-Box -> egs of how the ontologiescan be used in practice -straight lines between the A- and T-box denote an instance-of relationship
Integration of further online service accounts to our current system e.g. Health (RunKeeper), bank, government, social related accounts (Foursquare, Dropbox, Flickr)Metric: takes into account all the resulting weighted matches which were syntactically and/or semantically matched or partially matched>Threshold: determines whether two or more online profile refer to the same person-Evaluation: performed on 3 levels: syntactic matching, ii) semantic matching, and iii) a combination of
-Overall di.me Objective: integrating all personal data in a personal information sphere by a single, user-controlled single point of access: the di.meuserware.-Our part in di.me: WP3 – Objectives and Tasks mentioned in slide