際際滷shows by User: ebrahim_bagheri / http://www.slideshare.net/images/logo.gif 際際滷shows by User: ebrahim_bagheri / Tue, 17 Nov 2015 05:26:22 GMT 際際滷Share feed for 際際滷shows by User: ebrahim_bagheri Simplicity, Innovation and Entrepreneurship /slideshow/simplicity-innovation-and-entrepreneurship/55189996 presentation1-151117052622-lva1-app6891
In this presentation, I talk about how simple yet innovative ideas can solve complex problems. Many very computationally challenging problems can be solved using very simple solution and through the engagement of the public, the so called crowds! I talk about how the concept of gamification has been influential.]]>
In this presentation, I talk about how simple yet innovative ideas can solve complex problems. Many very computationally challenging problems can be solved using very simple solution and through the engagement of the public, the so called crowds! I talk about how the concept of gamification has been influential.]]> Tue, 17 Nov 2015 05:26:22 GMT /slideshow/simplicity-innovation-and-entrepreneurship/55189996 ebrahim_bagheri@slideshare.net(ebrahim_bagheri) Simplicity, Innovation and Entrepreneurship ebrahim_bagheri In this presentation, I talk about how simple yet innovative ideas can solve complex problems. Many very computationally challenging problems can be solved using very simple solution and through the engagement of the public, the so called crowds! I talk about how the concept of gamification has been influential. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/presentation1-151117052622-lva1-app6891-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> In this presentation, I talk about how simple yet innovative ideas can solve complex problems. Many very computationally challenging problems can be solved using very simple solution and through the engagement of the public, the so called crowds! I talk about how the concept of gamification has been influential.
Simplicity, Innovation and Entrepreneurship from ebrahim_bagheri
]]> 474 5 https://cdn.slidesharecdn.com/ss_thumbnails/presentation1-151117052622-lva1-app6891-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Modeling Semantics of Content on Twitter /slideshow/modeling-semantics-of-content-on-twitter/54552482 presentation1-151030043423-lva1-app6892
The microblogging service, Twitter, has gained wide popularity with over 300M active users and over 500M tweets per day. The unique characteristic of Twitter, only allowing short length messages to be communicated, has brought about interesting changes to how information is expressed and communicated by the users, i.e., the semantics of information when expressed on Twitter differ from when expressed on other medium. For instance, the word 'metal' when observed on Twitter carries a different semantic meaning, most likely referring to heavy metal music, as opposed to when used in other contexts where its predominant sense is the metal material. In this talk, I will discuss how the meaning and senses of words can be captured and modeled on Twitter to enable better and more efficient search, retrieval and recommendation of content.]]>
The microblogging service, Twitter, has gained wide popularity with over 300M active users and over 500M tweets per day. The unique characteristic of Twitter, only allowing short length messages to be communicated, has brought about interesting changes to how information is expressed and communicated by the users, i.e., the semantics of information when expressed on Twitter differ from when expressed on other medium. For instance, the word 'metal' when observed on Twitter carries a different semantic meaning, most likely referring to heavy metal music, as opposed to when used in other contexts where its predominant sense is the metal material. In this talk, I will discuss how the meaning and senses of words can be captured and modeled on Twitter to enable better and more efficient search, retrieval and recommendation of content.]]> Fri, 30 Oct 2015 04:34:23 GMT /slideshow/modeling-semantics-of-content-on-twitter/54552482 ebrahim_bagheri@slideshare.net(ebrahim_bagheri) Modeling Semantics of Content on Twitter ebrahim_bagheri The microblogging service, Twitter, has gained wide popularity with over 300M active users and over 500M tweets per day. The unique characteristic of Twitter, only allowing short length messages to be communicated, has brought about interesting changes to how information is expressed and communicated by the users, i.e., the semantics of information when expressed on Twitter differ from when expressed on other medium. For instance, the word 'metal' when observed on Twitter carries a different semantic meaning, most likely referring to heavy metal music, as opposed to when used in other contexts where its predominant sense is the metal material. In this talk, I will discuss how the meaning and senses of words can be captured and modeled on Twitter to enable better and more efficient search, retrieval and recommendation of content. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/presentation1-151030043423-lva1-app6892-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> The microblogging service, Twitter, has gained wide popularity with over 300M active users and over 500M tweets per day. The unique characteristic of Twitter, only allowing short length messages to be communicated, has brought about interesting changes to how information is expressed and communicated by the users, i.e., the semantics of information when expressed on Twitter differ from when expressed on other medium. For instance, the word &#39;metal&#39; when observed on Twitter carries a different semantic meaning, most likely referring to heavy metal music, as opposed to when used in other contexts where its predominant sense is the metal material. In this talk, I will discuss how the meaning and senses of words can be captured and modeled on Twitter to enable better and more efficient search, retrieval and recommendation of content.
Modeling Semantics of Content on Twitter from ebrahim_bagheri
]]> 491 4 https://cdn.slidesharecdn.com/ss_thumbnails/presentation1-151030043423-lva1-app6892-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Quality Metrics for Linked Open Data /slideshow/quality-metrics-for-linked-open-data/52314742 dexa2015-presentation-behkamal-150901221507-lva1-app6892
Structural syntactic metrics for RDF Datasets that correlate with high level quality deficiencies. The vision of the Linked Open Data (LOD) initiative is to provide a model for publishing data and meaningfully interlinking such dispersed but related data. Despite the importance of data quality for the successful growth of the LOD, only limited attention has been focused on quality of data prior to their publication on the LOD. This paper focuses on the systematic assessment of the quality of datasets prior to publication on the LOD cloud. To this end, we identify important quality deficiencies that need to be avoided and/or resolved prior to the publication of a dataset. We then propose a set of metrics to measure and identify these quality deficiencies in a dataset. This way, we enable the assessment and identification of undesirable quality characteristics of a dataset through our proposed metrics. 際際滷s for paper presentation at DEXA 2015: Behshid Behkamal, Mohsen Kahani, Ebrahim Bagheri: Quality Metrics for Linked Open Data. DEXA (1) 2015: 144-152 ]]>
Structural syntactic metrics for RDF Datasets that correlate with high level quality deficiencies. The vision of the Linked Open Data (LOD) initiative is to provide a model for publishing data and meaningfully interlinking such dispersed but related data. Despite the importance of data quality for the successful growth of the LOD, only limited attention has been focused on quality of data prior to their publication on the LOD. This paper focuses on the systematic assessment of the quality of datasets prior to publication on the LOD cloud. To this end, we identify important quality deficiencies that need to be avoided and/or resolved prior to the publication of a dataset. We then propose a set of metrics to measure and identify these quality deficiencies in a dataset. This way, we enable the assessment and identification of undesirable quality characteristics of a dataset through our proposed metrics. 際際滷s for paper presentation at DEXA 2015: Behshid Behkamal, Mohsen Kahani, Ebrahim Bagheri: Quality Metrics for Linked Open Data. DEXA (1) 2015: 144-152 ]]> Tue, 01 Sep 2015 22:15:07 GMT /slideshow/quality-metrics-for-linked-open-data/52314742 ebrahim_bagheri@slideshare.net(ebrahim_bagheri) Quality Metrics for Linked Open Data ebrahim_bagheri Structural syntactic metrics for RDF Datasets that correlate with high level quality deficiencies. The vision of the Linked Open Data (LOD) initiative is to provide a model for publishing data and meaningfully interlinking such dispersed but related data. Despite the importance of data quality for the successful growth of the LOD, only limited attention has been focused on quality of data prior to their publication on the LOD. This paper focuses on the systematic assessment of the quality of datasets prior to publication on the LOD cloud. To this end, we identify important quality deficiencies that need to be avoided and/or resolved prior to the publication of a dataset. We then propose a set of metrics to measure and identify these quality deficiencies in a dataset. This way, we enable the assessment and identification of undesirable quality characteristics of a dataset through our proposed metrics. 際際滷s for paper presentation at DEXA 2015: Behshid Behkamal, Mohsen Kahani, Ebrahim Bagheri: Quality Metrics for Linked Open Data. DEXA (1) 2015: 144-152 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/dexa2015-presentation-behkamal-150901221507-lva1-app6892-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Structural syntactic metrics for RDF Datasets that correlate with high level quality deficiencies. The vision of the Linked Open Data (LOD) initiative is to provide a model for publishing data and meaningfully interlinking such dispersed but related data. Despite the importance of data quality for the successful growth of the LOD, only limited attention has been focused on quality of data prior to their publication on the LOD. This paper focuses on the systematic assessment of the quality of datasets prior to publication on the LOD cloud. To this end, we identify important quality deficiencies that need to be avoided and/or resolved prior to the publication of a dataset. We then propose a set of metrics to measure and identify these quality deficiencies in a dataset. This way, we enable the assessment and identification of undesirable quality characteristics of a dataset through our proposed metrics. 際際滷s for paper presentation at DEXA 2015: Behshid Behkamal, Mohsen Kahani, Ebrahim Bagheri: Quality Metrics for Linked Open Data. DEXA (1) 2015: 144-152
Quality Metrics for Linked Open Data from ebrahim_bagheri
]]> 737 8 https://cdn.slidesharecdn.com/ss_thumbnails/dexa2015-presentation-behkamal-150901221507-lva1-app6892-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Filtering Inaccurate Entity Co-references on the Linked Open Data /slideshow/filtering-inaccurate-entity-coreferences-on-the-linked-open-data/52207673 dexapresentationjohn-150829204048-lva1-app6891
A method for identifying incorrect sameAs links on the Linked Open Data cloud Details published in: John Cuzzola, Ebrahim Bagheri, Jelena Jovanovic: Filtering Inaccurate Entity Co-references on the Linked Open Data. DEXA (1) 2015: 128-143]]>
A method for identifying incorrect sameAs links on the Linked Open Data cloud Details published in: John Cuzzola, Ebrahim Bagheri, Jelena Jovanovic: Filtering Inaccurate Entity Co-references on the Linked Open Data. DEXA (1) 2015: 128-143]]> Sat, 29 Aug 2015 20:40:48 GMT /slideshow/filtering-inaccurate-entity-coreferences-on-the-linked-open-data/52207673 ebrahim_bagheri@slideshare.net(ebrahim_bagheri) Filtering Inaccurate Entity Co-references on the Linked Open Data ebrahim_bagheri A method for identifying incorrect sameAs links on the Linked Open Data cloud Details published in: John Cuzzola, Ebrahim Bagheri, Jelena Jovanovic: Filtering Inaccurate Entity Co-references on the Linked Open Data. DEXA (1) 2015: 128-143 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/dexapresentationjohn-150829204048-lva1-app6891-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> A method for identifying incorrect sameAs links on the Linked Open Data cloud Details published in: John Cuzzola, Ebrahim Bagheri, Jelena Jovanovic: Filtering Inaccurate Entity Co-references on the Linked Open Data. DEXA (1) 2015: 128-143
Filtering Inaccurate Entity Co-references on the Linked Open Data from ebrahim_bagheri
]]> 457 7 https://cdn.slidesharecdn.com/ss_thumbnails/dexapresentationjohn-150829204048-lva1-app6891-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 https://public.slidesharecdn.com/v2/images/profile-picture.png https://cdn.slidesharecdn.com/ss_thumbnails/presentation1-151117052622-lva1-app6891-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/simplicity-innovation-and-entrepreneurship/55189996 Simplicity, Innovation... https://cdn.slidesharecdn.com/ss_thumbnails/presentation1-151030043423-lva1-app6892-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/modeling-semantics-of-content-on-twitter/54552482 Modeling Semantics of ... https://cdn.slidesharecdn.com/ss_thumbnails/dexa2015-presentation-behkamal-150901221507-lva1-app6892-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/quality-metrics-for-linked-open-data/52314742 Quality Metrics for L...