際際滷shows by User: FaeghehHasibi / http://www.slideshare.net/images/logo.gif 際際滷shows by User: FaeghehHasibi / Sun, 08 Oct 2017 09:25:57 GMT 際際滷Share feed for 際際滷shows by User: FaeghehHasibi Semantic Search and Result Presentation with Entity Cards /slideshow/semantic-search-and-result-presentation-with-entity-cards-80573073/80573073 seatalk-171008092557
際際滷s of Search Engines Amsterdam (SEA) talk https://www.meetup.com/SEA-Search-Engines-Amsterdam/events/239659928/ Modern search engines have moved from the traditional ten blue links environment towards understanding searchers' intent and providing them with the focused responses; a paradigm that is referred to as semantic search. Semantic search is an umbrella term that encompasses various techniques, including but not limited to, query understanding, entity retrieval, and result presentation. In this talk, I will give a brief overview on each of these tasks, and further focus on the result presentation aspect. Specifically, I will present methods for generating content for entity cards, the informational panels that are presented at the right column of search engine results pages. I will end the talk by introducing a practical toolkit and dataset that are meant to foster research in this area.]]>
際際滷s of Search Engines Amsterdam (SEA) talk https://www.meetup.com/SEA-Search-Engines-Amsterdam/events/239659928/ Modern search engines have moved from the traditional ten blue links environment towards understanding searchers' intent and providing them with the focused responses; a paradigm that is referred to as semantic search. Semantic search is an umbrella term that encompasses various techniques, including but not limited to, query understanding, entity retrieval, and result presentation. In this talk, I will give a brief overview on each of these tasks, and further focus on the result presentation aspect. Specifically, I will present methods for generating content for entity cards, the informational panels that are presented at the right column of search engine results pages. I will end the talk by introducing a practical toolkit and dataset that are meant to foster research in this area.]]> Sun, 08 Oct 2017 09:25:57 GMT /slideshow/semantic-search-and-result-presentation-with-entity-cards-80573073/80573073 FaeghehHasibi@slideshare.net(FaeghehHasibi) Semantic Search and Result Presentation with Entity Cards FaeghehHasibi 際際滷s of Search Engines Amsterdam (SEA) talk https://www.meetup.com/SEA-Search-Engines-Amsterdam/events/239659928/ Modern search engines have moved from the traditional ten blue links environment towards understanding searchers' intent and providing them with the focused responses; a paradigm that is referred to as semantic search. Semantic search is an umbrella term that encompasses various techniques, including but not limited to, query understanding, entity retrieval, and result presentation. In this talk, I will give a brief overview on each of these tasks, and further focus on the result presentation aspect. Specifically, I will present methods for generating content for entity cards, the informational panels that are presented at the right column of search engine results pages. I will end the talk by introducing a practical toolkit and dataset that are meant to foster research in this area. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/seatalk-171008092557-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> 際際滷s of Search Engines Amsterdam (SEA) talk https://www.meetup.com/SEA-Search-Engines-Amsterdam/events/239659928/ Modern search engines have moved from the traditional ten blue links environment towards understanding searchers&#39; intent and providing them with the focused responses; a paradigm that is referred to as semantic search. Semantic search is an umbrella term that encompasses various techniques, including but not limited to, query understanding, entity retrieval, and result presentation. In this talk, I will give a brief overview on each of these tasks, and further focus on the result presentation aspect. Specifically, I will present methods for generating content for entity cards, the informational panels that are presented at the right column of search engine results pages. I will end the talk by introducing a practical toolkit and dataset that are meant to foster research in this area.
Semantic Search and Result Presentation with Entity Cards from Faegheh Hasibi
]]> 372 4 https://cdn.slidesharecdn.com/ss_thumbnails/seatalk-171008092557-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 Dynamic Factual Summaries for Entity Cards /slideshow/sigir2017dynes/78721297 sigir2017-dynes-170810052716
際際滷s for SIGIR 2017 paper "Dynamic Factual Summaries for Entity Cards" Entity cards are being used frequently in modern web search engines to offer a concise overview of an entity directly on the results page. These cards are composed of various elements, one of them being the entity summary: a selection of facts describing the entity from an underlying knowledge base. These summaries, while presenting a synopsis of the entity, can also directly address users information needs. In this paper, we make the first effort towards generating and evaluating such factual summaries. We introduce and address the novel problem of dynamic entity summarization for entity cards, and break it down to two specific subtasks: fact ranking and summary generation. We perform an extensive evaluation of our method using crowdsourcing. Our results show the effectiveness of our fact ranking approach and validate that users prefer dynamic summaries over static ones.]]>
際際滷s for SIGIR 2017 paper "Dynamic Factual Summaries for Entity Cards" Entity cards are being used frequently in modern web search engines to offer a concise overview of an entity directly on the results page. These cards are composed of various elements, one of them being the entity summary: a selection of facts describing the entity from an underlying knowledge base. These summaries, while presenting a synopsis of the entity, can also directly address users information needs. In this paper, we make the first effort towards generating and evaluating such factual summaries. We introduce and address the novel problem of dynamic entity summarization for entity cards, and break it down to two specific subtasks: fact ranking and summary generation. We perform an extensive evaluation of our method using crowdsourcing. Our results show the effectiveness of our fact ranking approach and validate that users prefer dynamic summaries over static ones.]]> Thu, 10 Aug 2017 05:27:16 GMT /slideshow/sigir2017dynes/78721297 FaeghehHasibi@slideshare.net(FaeghehHasibi) Dynamic Factual Summaries for Entity Cards FaeghehHasibi 際際滷s for SIGIR 2017 paper "Dynamic Factual Summaries for Entity Cards" Entity cards are being used frequently in modern web search engines to offer a concise overview of an entity directly on the results page. These cards are composed of various elements, one of them being the entity summary: a selection of facts describing the entity from an underlying knowledge base. These summaries, while presenting a synopsis of the entity, can also directly address users information needs. In this paper, we make the first effort towards generating and evaluating such factual summaries. We introduce and address the novel problem of dynamic entity summarization for entity cards, and break it down to two specific subtasks: fact ranking and summary generation. We perform an extensive evaluation of our method using crowdsourcing. Our results show the effectiveness of our fact ranking approach and validate that users prefer dynamic summaries over static ones. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/sigir2017-dynes-170810052716-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> 際際滷s for SIGIR 2017 paper &quot;Dynamic Factual Summaries for Entity Cards&quot; Entity cards are being used frequently in modern web search engines to offer a concise overview of an entity directly on the results page. These cards are composed of various elements, one of them being the entity summary: a selection of facts describing the entity from an underlying knowledge base. These summaries, while presenting a synopsis of the entity, can also directly address users information needs. In this paper, we make the first effort towards generating and evaluating such factual summaries. We introduce and address the novel problem of dynamic entity summarization for entity cards, and break it down to two specific subtasks: fact ranking and summary generation. We perform an extensive evaluation of our method using crowdsourcing. Our results show the effectiveness of our fact ranking approach and validate that users prefer dynamic summaries over static ones.
Dynamic Factual Summaries for Entity Cards from Faegheh Hasibi
]]> 869 7 https://cdn.slidesharecdn.com/ss_thumbnails/sigir2017-dynes-170810052716-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 Entity Linking in Queries: Efficiency vs. Effectiveness /slideshow/ecir2017erd/74938705 wednesday-session4-hasibi-170412145521
際際滷s for the ECIR 2017 paper "Entity Linking in Queries: Efficiency vs. Effectiveness" Identifying and disambiguating entity references in queries is one of the core enabling components for semantic search. While there is a large body of work on entity linking in documents, entity linking in queries poses new challenges due to the limited context the query provides coupled with the efficiency requirements of an online setting. Our goal is to gain a deeper understanding of how to approach entity linking in queries, with a special focus on how to strike a balance between effectiveness and efficiency. We divide the task of entity linking in queries to two main steps: candidate entity ranking and disambiguation, and explore both unsupervised and supervised alternatives for each step. Our main finding is that best overall performance (in terms of efficiency and effectiveness) can be achieved by employing supervised learning for the entity ranking step, while tackling disambiguation with a simple unsupervised algorithm. Using the Entity Recognition and Disambiguation Challenge platform, we further demonstrate that our recommended method achieves state-of-the-art performance.]]>
際際滷s for the ECIR 2017 paper "Entity Linking in Queries: Efficiency vs. Effectiveness" Identifying and disambiguating entity references in queries is one of the core enabling components for semantic search. While there is a large body of work on entity linking in documents, entity linking in queries poses new challenges due to the limited context the query provides coupled with the efficiency requirements of an online setting. Our goal is to gain a deeper understanding of how to approach entity linking in queries, with a special focus on how to strike a balance between effectiveness and efficiency. We divide the task of entity linking in queries to two main steps: candidate entity ranking and disambiguation, and explore both unsupervised and supervised alternatives for each step. Our main finding is that best overall performance (in terms of efficiency and effectiveness) can be achieved by employing supervised learning for the entity ranking step, while tackling disambiguation with a simple unsupervised algorithm. Using the Entity Recognition and Disambiguation Challenge platform, we further demonstrate that our recommended method achieves state-of-the-art performance.]]> Wed, 12 Apr 2017 14:55:20 GMT /slideshow/ecir2017erd/74938705 FaeghehHasibi@slideshare.net(FaeghehHasibi) Entity Linking in Queries: Efficiency vs. Effectiveness FaeghehHasibi 際際滷s for the ECIR 2017 paper "Entity Linking in Queries: Efficiency vs. Effectiveness" Identifying and disambiguating entity references in queries is one of the core enabling components for semantic search. While there is a large body of work on entity linking in documents, entity linking in queries poses new challenges due to the limited context the query provides coupled with the efficiency requirements of an online setting. Our goal is to gain a deeper understanding of how to approach entity linking in queries, with a special focus on how to strike a balance between effectiveness and efficiency. We divide the task of entity linking in queries to two main steps: candidate entity ranking and disambiguation, and explore both unsupervised and supervised alternatives for each step. Our main finding is that best overall performance (in terms of efficiency and effectiveness) can be achieved by employing supervised learning for the entity ranking step, while tackling disambiguation with a simple unsupervised algorithm. Using the Entity Recognition and Disambiguation Challenge platform, we further demonstrate that our recommended method achieves state-of-the-art performance. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/wednesday-session4-hasibi-170412145521-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> 際際滷s for the ECIR 2017 paper &quot;Entity Linking in Queries: Efficiency vs. Effectiveness&quot; Identifying and disambiguating entity references in queries is one of the core enabling components for semantic search. While there is a large body of work on entity linking in documents, entity linking in queries poses new challenges due to the limited context the query provides coupled with the efficiency requirements of an online setting. Our goal is to gain a deeper understanding of how to approach entity linking in queries, with a special focus on how to strike a balance between effectiveness and efficiency. We divide the task of entity linking in queries to two main steps: candidate entity ranking and disambiguation, and explore both unsupervised and supervised alternatives for each step. Our main finding is that best overall performance (in terms of efficiency and effectiveness) can be achieved by employing supervised learning for the entity ranking step, while tackling disambiguation with a simple unsupervised algorithm. Using the Entity Recognition and Disambiguation Challenge platform, we further demonstrate that our recommended method achieves state-of-the-art performance.
Entity Linking in Queries: Efficiency vs. Effectiveness from Faegheh Hasibi
]]> 792 4 https://cdn.slidesharecdn.com/ss_thumbnails/wednesday-session4-hasibi-170412145521-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 Exploiting Entity Linking in Queries For Entity Retrieval /slideshow/ictir2016-elr/66065744 ictir2016-elr-160915163341
際際滷s for the ICTIR 2016 paper: "Exploiting Entity Linking in Queries For Entity Retrieval" The premise of entity retrieval is to better answer search queries by returning specific entities instead of documents. Many queries mention particular entities; recognizing and linking them to the corresponding entry in a knowledge base is known as the task of entity linking in queries. In this paper we make a first attempt at bringing together these two, i.e., leveraging entity annotations of queries in the entity retrieval model. We introduce a new probabilistic component and show how it can be applied on top of any term based entity retrieval model that can be emulated in the Markov Random Field framework, including language models, sequential dependence models, as well as their fielded variations. Using a standard entity retrieval test collection, we show that our extension brings consistent improvements over all baseline methods, including the current state-of-the-art. We further show that our extension is robust against parameter settings.]]>
際際滷s for the ICTIR 2016 paper: "Exploiting Entity Linking in Queries For Entity Retrieval" The premise of entity retrieval is to better answer search queries by returning specific entities instead of documents. Many queries mention particular entities; recognizing and linking them to the corresponding entry in a knowledge base is known as the task of entity linking in queries. In this paper we make a first attempt at bringing together these two, i.e., leveraging entity annotations of queries in the entity retrieval model. We introduce a new probabilistic component and show how it can be applied on top of any term based entity retrieval model that can be emulated in the Markov Random Field framework, including language models, sequential dependence models, as well as their fielded variations. Using a standard entity retrieval test collection, we show that our extension brings consistent improvements over all baseline methods, including the current state-of-the-art. We further show that our extension is robust against parameter settings.]]> Thu, 15 Sep 2016 16:33:41 GMT /slideshow/ictir2016-elr/66065744 FaeghehHasibi@slideshare.net(FaeghehHasibi) Exploiting Entity Linking in Queries For Entity Retrieval FaeghehHasibi 際際滷s for the ICTIR 2016 paper: "Exploiting Entity Linking in Queries For Entity Retrieval" The premise of entity retrieval is to better answer search queries by returning specific entities instead of documents. Many queries mention particular entities; recognizing and linking them to the corresponding entry in a knowledge base is known as the task of entity linking in queries. In this paper we make a first attempt at bringing together these two, i.e., leveraging entity annotations of queries in the entity retrieval model. We introduce a new probabilistic component and show how it can be applied on top of any term based entity retrieval model that can be emulated in the Markov Random Field framework, including language models, sequential dependence models, as well as their fielded variations. Using a standard entity retrieval test collection, we show that our extension brings consistent improvements over all baseline methods, including the current state-of-the-art. We further show that our extension is robust against parameter settings. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/ictir2016-elr-160915163341-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> 際際滷s for the ICTIR 2016 paper: &quot;Exploiting Entity Linking in Queries For Entity Retrieval&quot; The premise of entity retrieval is to better answer search queries by returning specific entities instead of documents. Many queries mention particular entities; recognizing and linking them to the corresponding entry in a knowledge base is known as the task of entity linking in queries. In this paper we make a first attempt at bringing together these two, i.e., leveraging entity annotations of queries in the entity retrieval model. We introduce a new probabilistic component and show how it can be applied on top of any term based entity retrieval model that can be emulated in the Markov Random Field framework, including language models, sequential dependence models, as well as their fielded variations. Using a standard entity retrieval test collection, we show that our extension brings consistent improvements over all baseline methods, including the current state-of-the-art. We further show that our extension is robust against parameter settings.
Exploiting Entity Linking in Queries For Entity Retrieval from Faegheh Hasibi
]]> 1791 7 https://cdn.slidesharecdn.com/ss_thumbnails/ictir2016-elr-160915163341-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 On the Reproducibility of the TAGME entity linking system /slideshow/tagmerep/59891025 ecir2016-tagme-160322162330
際際滷 for the ECIR '16 paper: On the reproducibility of the TAGME Entity Linking System Reproducibility is a fundamental requirement of scientific research. In this paper, we examine the repeatability, reproducibility, and generalizability of TAGME, one of the most popular entity linking systems. By comparing results obtained from its public API with (re)implementations from scratch, we obtain the following findings. The results reported in the TAGME paper cannot be repeated due to the unavailability of data sources. Part of the results are reproducible through the provided API, while the rest are not reproducible. We further show that the TAGME approach is generalizable to the task of entity linking in queries. Finally, we provide insights gained during this process and formulate lessons learned to inform future reducibility efforts.]]>
際際滷 for the ECIR '16 paper: On the reproducibility of the TAGME Entity Linking System Reproducibility is a fundamental requirement of scientific research. In this paper, we examine the repeatability, reproducibility, and generalizability of TAGME, one of the most popular entity linking systems. By comparing results obtained from its public API with (re)implementations from scratch, we obtain the following findings. The results reported in the TAGME paper cannot be repeated due to the unavailability of data sources. Part of the results are reproducible through the provided API, while the rest are not reproducible. We further show that the TAGME approach is generalizable to the task of entity linking in queries. Finally, we provide insights gained during this process and formulate lessons learned to inform future reducibility efforts.]]> Tue, 22 Mar 2016 16:23:30 GMT /slideshow/tagmerep/59891025 FaeghehHasibi@slideshare.net(FaeghehHasibi) On the Reproducibility of the TAGME entity linking system FaeghehHasibi 際際滷 for the ECIR '16 paper: On the reproducibility of the TAGME Entity Linking System Reproducibility is a fundamental requirement of scientific research. In this paper, we examine the repeatability, reproducibility, and generalizability of TAGME, one of the most popular entity linking systems. By comparing results obtained from its public API with (re)implementations from scratch, we obtain the following findings. The results reported in the TAGME paper cannot be repeated due to the unavailability of data sources. Part of the results are reproducible through the provided API, while the rest are not reproducible. We further show that the TAGME approach is generalizable to the task of entity linking in queries. Finally, we provide insights gained during this process and formulate lessons learned to inform future reducibility efforts. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/ecir2016-tagme-160322162330-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> 際際滷 for the ECIR &#39;16 paper: On the reproducibility of the TAGME Entity Linking System Reproducibility is a fundamental requirement of scientific research. In this paper, we examine the repeatability, reproducibility, and generalizability of TAGME, one of the most popular entity linking systems. By comparing results obtained from its public API with (re)implementations from scratch, we obtain the following findings. The results reported in the TAGME paper cannot be repeated due to the unavailability of data sources. Part of the results are reproducible through the provided API, while the rest are not reproducible. We further show that the TAGME approach is generalizable to the task of entity linking in queries. Finally, we provide insights gained during this process and formulate lessons learned to inform future reducibility efforts.
On the Reproducibility of the TAGME entity linking system from Faegheh Hasibi
]]> 1824 7 https://cdn.slidesharecdn.com/ss_thumbnails/ecir2016-tagme-160322162330-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 Being a PhD student: Experiences and Challenges /slideshow/phdguidance/59686945 phd-guidance-160317163537
These slides provide some guidance to the prospective PhD students. The content reflects my personal experiences together with useful feedbacks I received from my colleagues/friends.]]>
These slides provide some guidance to the prospective PhD students. The content reflects my personal experiences together with useful feedbacks I received from my colleagues/friends.]]> Thu, 17 Mar 2016 16:35:37 GMT /slideshow/phdguidance/59686945 FaeghehHasibi@slideshare.net(FaeghehHasibi) Being a PhD student: Experiences and Challenges FaeghehHasibi These slides provide some guidance to the prospective PhD students. The content reflects my personal experiences together with useful feedbacks I received from my colleagues/friends. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/phd-guidance-160317163537-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> These slides provide some guidance to the prospective PhD students. The content reflects my personal experiences together with useful feedbacks I received from my colleagues/friends.
Being a PhD student: Experiences and Challenges from Faegheh Hasibi
]]> 3559 8 https://cdn.slidesharecdn.com/ss_thumbnails/phd-guidance-160317163537-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 Entity Linking in Queries: Tasks and Evaluation /FaeghehHasibi/icitir2015elq icitir2015-elq-151205013314-lva1-app6891
際際滷s for the ICTIR 2015 paper "Entity Linking in Queries: Tasks and Evaluation" Annotating queries with entities is one of the core problem areas in query understanding. While seeming similar, the task of entity linking in queries is different from entity linking in documents and requires a methodological departure due to the inherent ambiguity of queries. We differentiate between two specific tasks, semantic mapping and interpretation finding, discuss current evaluation methodology, and propose refinements. We examine publicly available datasets for these tasks and introduce a new manually curated dataset for interpretation finding. To further deepen the understanding of task differences, we present a set of approaches for effectively addressing these tasks and report on experimental results.]]>
際際滷s for the ICTIR 2015 paper "Entity Linking in Queries: Tasks and Evaluation" Annotating queries with entities is one of the core problem areas in query understanding. While seeming similar, the task of entity linking in queries is different from entity linking in documents and requires a methodological departure due to the inherent ambiguity of queries. We differentiate between two specific tasks, semantic mapping and interpretation finding, discuss current evaluation methodology, and propose refinements. We examine publicly available datasets for these tasks and introduce a new manually curated dataset for interpretation finding. To further deepen the understanding of task differences, we present a set of approaches for effectively addressing these tasks and report on experimental results.]]> Sat, 05 Dec 2015 01:33:14 GMT /FaeghehHasibi/icitir2015elq FaeghehHasibi@slideshare.net(FaeghehHasibi) Entity Linking in Queries: Tasks and Evaluation FaeghehHasibi 際際滷s for the ICTIR 2015 paper "Entity Linking in Queries: Tasks and Evaluation" Annotating queries with entities is one of the core problem areas in query understanding. While seeming similar, the task of entity linking in queries is different from entity linking in documents and requires a methodological departure due to the inherent ambiguity of queries. We differentiate between two specific tasks, semantic mapping and interpretation finding, discuss current evaluation methodology, and propose refinements. We examine publicly available datasets for these tasks and introduce a new manually curated dataset for interpretation finding. To further deepen the understanding of task differences, we present a set of approaches for effectively addressing these tasks and report on experimental results. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/icitir2015-elq-151205013314-lva1-app6891-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> 際際滷s for the ICTIR 2015 paper &quot;Entity Linking in Queries: Tasks and Evaluation&quot; Annotating queries with entities is one of the core problem areas in query understanding. While seeming similar, the task of entity linking in queries is different from entity linking in documents and requires a methodological departure due to the inherent ambiguity of queries. We differentiate between two specific tasks, semantic mapping and interpretation finding, discuss current evaluation methodology, and propose refinements. We examine publicly available datasets for these tasks and introduce a new manually curated dataset for interpretation finding. To further deepen the understanding of task differences, we present a set of approaches for effectively addressing these tasks and report on experimental results.
Entity Linking in Queries: Tasks and Evaluation from Faegheh Hasibi
]]> 939 9 https://cdn.slidesharecdn.com/ss_thumbnails/icitir2015-elq-151205013314-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 Yalda night /slideshow/yalda-night/55839243 yaldanight-151205012819-lva1-app6892
Yalda is one of the most celebrated traditional events in Iran which marks the longest night of the year. Every year, Yalda takes happen at 21st of December, which is close to when Christmas is celebrated. [Description is taken from https://en.wikipedia.org/wiki/Yald%C4%81]]]>
Yalda is one of the most celebrated traditional events in Iran which marks the longest night of the year. Every year, Yalda takes happen at 21st of December, which is close to when Christmas is celebrated. [Description is taken from https://en.wikipedia.org/wiki/Yald%C4%81]]]> Sat, 05 Dec 2015 01:28:19 GMT /slideshow/yalda-night/55839243 FaeghehHasibi@slideshare.net(FaeghehHasibi) Yalda night FaeghehHasibi Yalda is one of the most celebrated traditional events in Iran which marks the longest night of the year. Every year, Yalda takes happen at 21st of December, which is close to when Christmas is celebrated. [Description is taken from https://en.wikipedia.org/wiki/Yald%C4%81] <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/yaldanight-151205012819-lva1-app6892-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Yalda is one of the most celebrated traditional events in Iran which marks the longest night of the year. Every year, Yalda takes happen at 21st of December, which is close to when Christmas is celebrated. [Description is taken from https://en.wikipedia.org/wiki/Yald%C4%81]
Yalda night from Faegheh Hasibi
]]> 3783 7 https://cdn.slidesharecdn.com/ss_thumbnails/yaldanight-151205012819-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 https://cdn.slidesharecdn.com/profile-photo-FaeghehHasibi-48x48.jpg?cb=1620402423 hasibi.com/ https://cdn.slidesharecdn.com/ss_thumbnails/seatalk-171008092557-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/semantic-search-and-result-presentation-with-entity-cards-80573073/80573073 Semantic Search and Re... https://cdn.slidesharecdn.com/ss_thumbnails/sigir2017-dynes-170810052716-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/sigir2017dynes/78721297 Dynamic Factual Summar... https://cdn.slidesharecdn.com/ss_thumbnails/wednesday-session4-hasibi-170412145521-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/ecir2017erd/74938705 Entity Linking in Quer...