The MUCKE project aims to develop an image retrieval framework. It involves processing text and images to extract concepts and annotate images with semantic information. The project collects large datasets of images and text and processes the data using entity recognition, concept similarity, and image description techniques. It also aims to provide diversified search results by exploiting the hierarchical structure of the YAGO ontology. A demonstration of the image annotation and retrieval capabilities is shown.
The Agile Business Gap is created in medium to large organisations when "Agile" is initiated by an organisations development team. The first part of this Gap is just terminology where "agile" to a business has the dictionary meaning of "able to move quickly and easily" while "Agile" to a software development team has a very different meaning. The next part of the Gap is exposed as an "Agile" development team starts to demand a different way of operating beyond the development function and impacts everything from product management activities, business case development, financial planning, marketing messaging and operational planning.
"Agile" development is very effective at delivering smaller usable parts of a product to the market in shorter time frames, yet these shorter timeframes are not immediately compatible with the rest of the enterprise.
About the Speaker:
Nick Coster, co-founder of Brainmates, Australia's leading provider of Product Management consulting and training services. He has been working in various Product Management roles since 1996, across a range of product types and industries. At Brainmates he's the Head of Training services and delivers most of the training courses that Brainmates offers as well as facilitates collaborative workshops with clients. He believes there is a better way to deliver products that customers love and at Brainmates they are constantly learning from our experiences to explore better approaches.
Upcoming Events
Reserve your seat for the next AIPMM webinar. Visit: http://aipmm.com/aipmm_webinars/.
Want To Certify Your Team?
If you have a product team of 10 or more that you want to certify, visit: http://bit.ly/1bzjUYB.
About AIPMM
The AIPMM is the hub of all things product management. It is where product professionals go for answers. With members in over 65 countries, it is the worldwide certifying body of product team professionals.
It is the world's largest professional organization of product managers, brand managers, product marketing managers and other product team professionals who are responsible for guiding their organizations, or clients, through a constantly changing business landscape.
AIPMM's certification programs are internationally recognized because they allow product professionals to demonstrate their expertise and provide corporate members an assurance that their product management and marketing teams are operating at a high competency level.
Visit http://www.aipmm.com.
Call For Speakers: http://bit.ly/1b006vm
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LinkedIn: http://www.linkedin.com/company/aipmm
Membership: http://www.aipmm.com/join.php
Certification: http://aipmm.com/html/certification
Articles: http://www.aipmm.com/html/newsletter/article.ph
6WINDGate™ - Powering the New-Generation of IPsec Gateways6WIND
6WINDGate™ for IPsec Gateways:
- High performance IPsec stack to sustain encrypted traffic over several tens of thousands of IPsec tunnels with low-latency
- Optimal use of software and hardware crypto-acceleration for best price/performance
- High-capacity IKE control plane to manage several tens of thousands of IKE sessions on a single server
- High capacity for encapsulation protocols such as VLAN, PPP, L2TP and GRE…
- High performance and scalable IPv4 and IPv6 forwarding with virtual routing support for a large number of instances
- High performance and capacity firewall and NAT
The Agile Business Gap is created in medium to large organisations when "Agile" is initiated by an organisations development team. The first part of this Gap is just terminology where "agile" to a business has the dictionary meaning of "able to move quickly and easily" while "Agile" to a software development team has a very different meaning. The next part of the Gap is exposed as an "Agile" development team starts to demand a different way of operating beyond the development function and impacts everything from product management activities, business case development, financial planning, marketing messaging and operational planning.
"Agile" development is very effective at delivering smaller usable parts of a product to the market in shorter time frames, yet these shorter timeframes are not immediately compatible with the rest of the enterprise.
About the Speaker:
Nick Coster, co-founder of Brainmates, Australia's leading provider of Product Management consulting and training services. He has been working in various Product Management roles since 1996, across a range of product types and industries. At Brainmates he's the Head of Training services and delivers most of the training courses that Brainmates offers as well as facilitates collaborative workshops with clients. He believes there is a better way to deliver products that customers love and at Brainmates they are constantly learning from our experiences to explore better approaches.
Upcoming Events
Reserve your seat for the next AIPMM webinar. Visit: http://aipmm.com/aipmm_webinars/.
Want To Certify Your Team?
If you have a product team of 10 or more that you want to certify, visit: http://bit.ly/1bzjUYB.
About AIPMM
The AIPMM is the hub of all things product management. It is where product professionals go for answers. With members in over 65 countries, it is the worldwide certifying body of product team professionals.
It is the world's largest professional organization of product managers, brand managers, product marketing managers and other product team professionals who are responsible for guiding their organizations, or clients, through a constantly changing business landscape.
AIPMM's certification programs are internationally recognized because they allow product professionals to demonstrate their expertise and provide corporate members an assurance that their product management and marketing teams are operating at a high competency level.
Visit http://www.aipmm.com.
Call For Speakers: http://bit.ly/1b006vm
Subscribe: http://www.aipmm.com/subscribe
LinkedIn: http://www.linkedin.com/company/aipmm
Membership: http://www.aipmm.com/join.php
Certification: http://aipmm.com/html/certification
Articles: http://www.aipmm.com/html/newsletter/article.ph
6WINDGate™ - Powering the New-Generation of IPsec Gateways6WIND
6WINDGate™ for IPsec Gateways:
- High performance IPsec stack to sustain encrypted traffic over several tens of thousands of IPsec tunnels with low-latency
- Optimal use of software and hardware crypto-acceleration for best price/performance
- High-capacity IKE control plane to manage several tens of thousands of IKE sessions on a single server
- High capacity for encapsulation protocols such as VLAN, PPP, L2TP and GRE…
- High performance and scalable IPv4 and IPv6 forwarding with virtual routing support for a large number of instances
- High performance and capacity firewall and NAT
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
RECURRENT FEATURE GROUPING AND CLASSIFICATION MODEL FOR ACTION MODEL PREDICTI...IJDKP
Content based retrieval has an advantage of higher prediction accuracy as compared to tagging based approach. However, the complexity in its representation and classification approach, results in lower processing accuracy and computation overhead. The correlative nature of the feature data are un-explored in the conventional modeling, where all the data features are taken as a set of feature values to give a decision. The recurrent feature class attribute is observed for the feature regrouping in action model prediction. In this paper a co-relative information, bounding grouping approach is suggested for action model prediction in CBMR application. The co-relative recurrent feature mapping results in faster retrieval process as compared to the conventional retrieval system.
RECURRENT FEATURE GROUPING AND CLASSIFICATION MODEL FOR ACTION MODEL PREDICTI...IJDKP
Content based retrieval has an advantage of higher prediction accuracy as compared to tagging based approach. However, the complexity in its representation and classification approach, results in lower processing accuracy and computation overhead. The correlative nature of the feature data are un-explored in the conventional modeling, where all the data features are taken as a set of feature values to give a decision. The recurrent feature class attribute is observed for the feature regrouping in action model prediction. In this paper a co-relative information, bounding grouping approach is suggested for action model prediction in CBMR application. The co-relative recurrent feature mapping results in faster retrieval process as compared to the conventional retrieval system.
RESEARCH PROPOSAL ON ENHANCING AUTOMATIC IMAGE CAPTIONING SYSTEM LSTM.pdfMUHUMUZAONAN1
In this research study, the researchers aim to investigate and address these challenges by proposing techniques and architectures for enhancing image captioning systems using CNNs and LSTMs. Specifically, the researchers will focus on developing a system that generates accurate and semantically meaningful captions for a wide range of images. By doing so, the researchers aim to contribute to the development of more effective and reliable image captioning systems.
Linked Data Mapping Cultures
An Evaluation of Metadata Usage and Distribution
in a Linked Data Environment
Konstantin Baierer, Evelyn Dröge, Vivien Petras, Violeta Trkulja
Berlin School of Library and Information Science, Humboldt-Universität zu Berlin
Presentation at the International Conference on Dublin Core and Metadata Applications
Austin, October 9, 2014
Adoption of MDE technologies (and techniques) could be dis- cussed within the context of existing technology acceptance models (TAMs). For instance, Davis’ basic TAM model [4] emphasizes (perceived) usefulness and ease of use. While these factors are clearly relevant, we aim at a more refined view by paying special attention to how MDE, at this stage, is driven by research and university teaching. That is, we describe the challenge of improving chances of MDE adoption (i.e., improved ‘adoptability’) in terms of maturing three legs of an ‘adoption chair’: i) reproducibility of research re- sults; ii) reusability of essential technologies; iii) teachability of the underlying techniques.
An efficient educational data mining approach to support e-learningVenu Madhav
The e-learning is a recent development that has
emerged in the educational system due to the growth of the
information technology. The common challenges involved
in The e-learning platform include the collection and
annotation of the learning materials, organization of the
knowledge in a useful way, the retrieval and discovery of
the useful learning materials from the knowledge space in a
more significant way, and the delivery of the adaptive and
personalized learning materials. In order to handle these
challenges, the proposed system is developed using five
different steps of knowledge input such as the annotation of
the learning materials, creation of knowledge space,
indexing of learning materials using the multi-dimensional
knowledge and XML structure to generate a knowledge
grid and the retrieval of learning materials performed by
matching the user query with the indexed database and
ontology. The process is carried out in two modules such as
the server module and client module. The proposed
approach is evaluated using various parameters such as the
precision, recall and F-measure. Comprehensive results are
achieved by varying the keywords, number of documents
and the K-size. The proposed approach has yielded
excellent results by obtaining the higher evaluation metric,
together with an average precision of 0.81, average
Multimedia information retrieval using artificial neural networkIAESIJAI
The importance of the multimedia information retrieval (MIR) is highlighted
by the extensive amount of the information on the internet. Image, audio,
video, and text are all examples of the characteristics of the raw multimedia
data. It is greatly challenging to represent a concept of human perception and
how the machine-level language can grasp it (semantic gap of MIR).
However, this paper aims to improve the information retrieval model that
retrieves data from multimedia. This can be implemented by leveraging the
use of variety of algorithms that go through training and testing to extract the
model. One of these algorithms extracts text information based on the query
language's nature as the vector space model (VSM) and the latent semantic
index (LSI) were used. The other technique uses curvelet decomposition and
statistic parameters like mean, standard deviation, and signal energy to
recover these properties. Additionally, a discrete wavelet transforms (DWT)
and signal characteristics-based method is used to retrieve audio signals.
Finally, the neural network learning is modeled and trained on a collection
of different multimedia images. The learned features have been utilized for
presenting a highly sufficient system of multimedia retrieval which operates
for a large set of multi-modal datasets.
Knowledge Technologies group at CefrielIrene Celino
Main research and innovation interests of the Knowledge technologies groups at Cefriel: Semantic Interoperability and Human Computation. Summary of our research lines,our approach, our offer and our experience in cooperative R&D projects.
In this presentation, we can see how we can use artificial intelligence in software engineering to develop faster and more efficient projects of the best quality.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
RECURRENT FEATURE GROUPING AND CLASSIFICATION MODEL FOR ACTION MODEL PREDICTI...IJDKP
Content based retrieval has an advantage of higher prediction accuracy as compared to tagging based approach. However, the complexity in its representation and classification approach, results in lower processing accuracy and computation overhead. The correlative nature of the feature data are un-explored in the conventional modeling, where all the data features are taken as a set of feature values to give a decision. The recurrent feature class attribute is observed for the feature regrouping in action model prediction. In this paper a co-relative information, bounding grouping approach is suggested for action model prediction in CBMR application. The co-relative recurrent feature mapping results in faster retrieval process as compared to the conventional retrieval system.
RECURRENT FEATURE GROUPING AND CLASSIFICATION MODEL FOR ACTION MODEL PREDICTI...IJDKP
Content based retrieval has an advantage of higher prediction accuracy as compared to tagging based approach. However, the complexity in its representation and classification approach, results in lower processing accuracy and computation overhead. The correlative nature of the feature data are un-explored in the conventional modeling, where all the data features are taken as a set of feature values to give a decision. The recurrent feature class attribute is observed for the feature regrouping in action model prediction. In this paper a co-relative information, bounding grouping approach is suggested for action model prediction in CBMR application. The co-relative recurrent feature mapping results in faster retrieval process as compared to the conventional retrieval system.
RESEARCH PROPOSAL ON ENHANCING AUTOMATIC IMAGE CAPTIONING SYSTEM LSTM.pdfMUHUMUZAONAN1
In this research study, the researchers aim to investigate and address these challenges by proposing techniques and architectures for enhancing image captioning systems using CNNs and LSTMs. Specifically, the researchers will focus on developing a system that generates accurate and semantically meaningful captions for a wide range of images. By doing so, the researchers aim to contribute to the development of more effective and reliable image captioning systems.
Linked Data Mapping Cultures
An Evaluation of Metadata Usage and Distribution
in a Linked Data Environment
Konstantin Baierer, Evelyn Dröge, Vivien Petras, Violeta Trkulja
Berlin School of Library and Information Science, Humboldt-Universität zu Berlin
Presentation at the International Conference on Dublin Core and Metadata Applications
Austin, October 9, 2014
Adoption of MDE technologies (and techniques) could be dis- cussed within the context of existing technology acceptance models (TAMs). For instance, Davis’ basic TAM model [4] emphasizes (perceived) usefulness and ease of use. While these factors are clearly relevant, we aim at a more refined view by paying special attention to how MDE, at this stage, is driven by research and university teaching. That is, we describe the challenge of improving chances of MDE adoption (i.e., improved ‘adoptability’) in terms of maturing three legs of an ‘adoption chair’: i) reproducibility of research re- sults; ii) reusability of essential technologies; iii) teachability of the underlying techniques.
An efficient educational data mining approach to support e-learningVenu Madhav
The e-learning is a recent development that has
emerged in the educational system due to the growth of the
information technology. The common challenges involved
in The e-learning platform include the collection and
annotation of the learning materials, organization of the
knowledge in a useful way, the retrieval and discovery of
the useful learning materials from the knowledge space in a
more significant way, and the delivery of the adaptive and
personalized learning materials. In order to handle these
challenges, the proposed system is developed using five
different steps of knowledge input such as the annotation of
the learning materials, creation of knowledge space,
indexing of learning materials using the multi-dimensional
knowledge and XML structure to generate a knowledge
grid and the retrieval of learning materials performed by
matching the user query with the indexed database and
ontology. The process is carried out in two modules such as
the server module and client module. The proposed
approach is evaluated using various parameters such as the
precision, recall and F-measure. Comprehensive results are
achieved by varying the keywords, number of documents
and the K-size. The proposed approach has yielded
excellent results by obtaining the higher evaluation metric,
together with an average precision of 0.81, average
Multimedia information retrieval using artificial neural networkIAESIJAI
The importance of the multimedia information retrieval (MIR) is highlighted
by the extensive amount of the information on the internet. Image, audio,
video, and text are all examples of the characteristics of the raw multimedia
data. It is greatly challenging to represent a concept of human perception and
how the machine-level language can grasp it (semantic gap of MIR).
However, this paper aims to improve the information retrieval model that
retrieves data from multimedia. This can be implemented by leveraging the
use of variety of algorithms that go through training and testing to extract the
model. One of these algorithms extracts text information based on the query
language's nature as the vector space model (VSM) and the latent semantic
index (LSI) were used. The other technique uses curvelet decomposition and
statistic parameters like mean, standard deviation, and signal energy to
recover these properties. Additionally, a discrete wavelet transforms (DWT)
and signal characteristics-based method is used to retrieve audio signals.
Finally, the neural network learning is modeled and trained on a collection
of different multimedia images. The learned features have been utilized for
presenting a highly sufficient system of multimedia retrieval which operates
for a large set of multi-modal datasets.
Knowledge Technologies group at CefrielIrene Celino
Main research and innovation interests of the Knowledge technologies groups at Cefriel: Semantic Interoperability and Human Computation. Summary of our research lines,our approach, our offer and our experience in cooperative R&D projects.
In this presentation, we can see how we can use artificial intelligence in software engineering to develop faster and more efficient projects of the best quality.
The habilitation thesis presents two main directions:
1. Exploiting data from social networks (Twitter, Facebook, Flickr, etc.) - creating resources for text and image processing (classification, retrieval, credibility, diversification, etc.);
2. Creating applications with new technologies: augmented reality (eLearning, games, smart museums, gastronomy, etc.), virtual reality (eLearning and games), speech processing with Amazon Alexa (eLearning, entertainment, IoT, etc.).
The work was validated with good results in evaluation campaigns like CLEF (Question Answering, Image CLEF, LifeCLEF, etc.), SemEval (Sentiment and Emotion in text, Anorexia, etc.).
After presenting the notion of augmented reality, the main areas of applicability are listed and some of the students' projects from the Faculty of Computer Science in Iasi are shown.
This presentation, created by Syed Faiz ul Hassan, explores the profound influence of media on public perception and behavior. It delves into the evolution of media from oral traditions to modern digital and social media platforms. Key topics include the role of media in information propagation, socialization, crisis awareness, globalization, and education. The presentation also examines media influence through agenda setting, propaganda, and manipulative techniques used by advertisers and marketers. Furthermore, it highlights the impact of surveillance enabled by media technologies on personal behavior and preferences. Through this comprehensive overview, the presentation aims to shed light on how media shapes collective consciousness and public opinion.
Acorn Recovery: Restore IT infra within minutesIP ServerOne
Introducing Acorn Recovery as a Service, a simple, fast, and secure managed disaster recovery (DRaaS) by IP ServerOne. A DR solution that helps restore your IT infra within minutes.
Have you ever wondered how search works while visiting an e-commerce site, internal website, or searching through other types of online resources? Look no further than this informative session on the ways that taxonomies help end-users navigate the internet! Hear from taxonomists and other information professionals who have first-hand experience creating and working with taxonomies that aid in navigation, search, and discovery across a range of disciplines.
This presentation by Morris Kleiner (University of Minnesota), was made during the discussion “Competition and Regulation in Professions and Occupations” held at the Working Party No. 2 on Competition and Regulation on 10 June 2024. More papers and presentations on the topic can be found out at oe.cd/crps.
This presentation was uploaded with the author’s consent.
0x01 - Newton's Third Law: Static vs. Dynamic AbusersOWASP Beja
f you offer a service on the web, odds are that someone will abuse it. Be it an API, a SaaS, a PaaS, or even a static website, someone somewhere will try to figure out a way to use it to their own needs. In this talk we'll compare measures that are effective against static attackers and how to battle a dynamic attacker who adapts to your counter-measures.
About the Speaker
===============
Diogo Sousa, Engineering Manager @ Canonical
An opinionated individual with an interest in cryptography and its intersection with secure software development.
Sharpen existing tools or get a new toolbox? Contemporary cluster initiatives...Orkestra
UIIN Conference, Madrid, 27-29 May 2024
James Wilson, Orkestra and Deusto Business School
Emily Wise, Lund University
Madeline Smith, The Glasgow School of Art
Sharpen existing tools or get a new toolbox? Contemporary cluster initiatives...
Diversification in an Image Retrieval System
1. MUCKE Project
• Iftene, A., Sirițeanu, A., Petic, M. How to Do
Diversification in an Image Retrieval System
• Laic, A., Iftene, A. Automatic Image Annotation
• Gherasim, L. M., Iftene, A. Extracting Background
Knowledge about World from Text.
ConsILR, September 18-19, 2014, Craiova
2. Content
MUCKE Team
The core
The data
Text processing
Image processing
Diversification
Problem
Demo
Automatic Image Annotation
ConsILR, September 18-19, 2014, Craiova
3. MUCKE Team
Bilkent University, Turkey
“Al. I. Cuza” University, Iasi, Romania
Vienna University of Technology, Austria
Center for Alternative and Atomic Energy, France
IMCS-50, 2014
5. The core
Text
Processing
Concept
similarity
Image
Processing
User
credibility
Raw multimedia and multilingual data
Output
Image
retrieval
framework
Semantic
Resources
ConsILR, September 18-19, 2014, Craiova
6. The data
Existing collections
A survey done and published online
ImageNet – 14 million annotated images
mediaEval – 3.2 million images
MIRFLICKR – 1 million annotated images
Wikipedia (DBpedia)
ClueWeb09/12
Text
Processing
Concept
similarity
Image
Processing
User
credibility
Raw multimedia and multilingual data
Output
Image
retrieval
framework
Semantic
Resources
New data
Aim: 100million annotated images
Crawling ongoing
ConsILR, September 18-19, 2014, Craiova
7. The data
Distributed crawling and replicated
storage
Text
Processing
Concept
similarity
Image
Processing
User
credibility
Raw multimedia and multilingual data
Output
Image
retrieval
framework
Semantic
Resources
ConsILR, September 18-19, 2014, Craiova
8. Text Processing
Text
Processing
Concept
similarity
Image
Processing
User
credibility
Raw multimedia and multilingual data
Output
Image
retrieval
framework
Semantic
Resources
Entity recognition
Disambiguation
Anaphora resolution
Combined with IR methods
Latent semantic retrieval
Explicit semantic retrieval
Components for:
English, French, German, Romanian
9. Image Processing
Text
Processing
Concept
similarity
Image
Processing
User
credibility
Raw multimedia and multilingual data
Output
Image
retrieval
framework
Semantic
Resources
Parsimonious image description
Large scale concept detection
Detector generalization
Across different datasets
Asses the use and utility of
Different local image descriptors
their combination with other properties (e.g.
color)
For optimal low-level image description
Adapted models for specialized tasks
Face / landmark recognition
11. Diversification – Problem definition
Search Results Diversification is an optimization
problem aiming to select a subset S of k items out of
the n available ones, such that, the diversity and the
relevance among the items of S is maximized. [1]
ConsILR, September 18-19, 2014, Craiova
12. Diversification – Proposed solution
Exploitation of semantic structures in order to
provide diverse and relevant results
Hierarchical structure of YAGO Concepts [6]:
IMCS-50, 2014
13. Performed steps
Deciding what terms in a query should be
used to query YAGO ontology.
Ranking and grouping the results retrieved
by YAGO ontology.
Choosing which YAGO entities to use in
crawling Flickr database.
Ranking the results so that we achieve both
relevance and diversity in the result set.
ConsILR, September 18-19, 2014, Craiova
17. Conclusions
Diversification can really improve quality of
search results.
There is still some work to do in order to
achieve good results in all the possible
scenarios
We need a large collection of annotated
images
We need performance algorithms which
provide the distance between images
ConsILR, September 18-19, 2014, Craiova
18. Thank you
MUCKE
Multimedia and User Credibility Knowledge Extraction
http://thor.info.uaic.ro/~mucke/
ConsILR, September 18-19, 2014, Craiova
19. Bibliography
[1] Drosou, M., Pitoura, E., Search Results Diversification. In SIGMOD, pages 41-47,
2010.
[2] Gollapudi, S., Sharma, A., An Axiomatic Approach for Result Diversification. In
WWW, pages 381-390, 2009.
[3] Carbonell, J. G., Goldstein, J., The use of MMR, diversity-based reranking for
reordering documents and producing summaries. In SIGIR, pages 335–336, 1998
[4] Clarke, C. L. A., Kolla, M., Cormack, G. V., Vechtomova, O., Ashkan, A., Büttcher, S.,
MacKinnon, I., Novelty and diversity in information retrieval evaluation. In SIGIR,
pages 659–666, 2008.
[5] Zheng, W., Wang, X., Fang, H., Cheng, H., Coverage-based search result
diversification, In Journal Information Retrieval, pages 433-457, 2012.
[6] YAGO2s: A High-Quality Knowledge Base, [Online] Available at http://www.mpi-inf.
mpg.de/departments/databases-and-information-systems/research/yago-naga/
yago/ [Last Accessed 27 June 2014].
[7] Cilibrasi, R., Vitanyi, P. M. B., The Google Similarity Distance. In IEEE TKDE, Vol.
19, Issue 3, pages 370-383, 2007.
[8] Kelleher, M., [Online] Available at http://www.smartinsights.com/email-marketing/
behavioural-email-marketing/which-top-5-strategies-drive-relevance-in-email-
marketing/ [Last Accessed 1 July 2014]
ConsILR, September 18-19, 2014, Craiova