ºÝºÝߣshows by User: shailajaswami9 / http://www.slideshare.net/images/logo.gif ºÝºÝߣshows by User: shailajaswami9 / Mon, 23 Jun 2014 04:19:40 GMT ºÝºÝߣShare feed for ºÝºÝߣshows by User: shailajaswami9 2014 IEEE project /slideshow/2014-project/36186742 projectlist-140623041940-phpapp01
list of IEEE project]]>
list of IEEE project]]> Mon, 23 Jun 2014 04:19:40 GMT /slideshow/2014-project/36186742 shailajaswami9@slideshare.net(shailajaswami9) 2014 IEEE project shailajaswami9 list of IEEE project <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/projectlist-140623041940-phpapp01-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> list of IEEE project
2014 IEEE project from Shailaja Swami
]]> 2832 3 https://cdn.slidesharecdn.com/ss_thumbnails/projectlist-140623041940-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds document White http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Deriving concept absed user profile /slideshow/deriving-concept-absed-user-profile/26447768 derivingconceptabseduserprofile-130923023544-phpapp02
User profiling is a fundamental component of any personalization applications. Most existing user profiling strategies are based on objects that users are interested in (i.e., positive preferences), but not the objects that users dislike (i.e., negative preferences). In this paper, we focus on search engine personalization and develop several concept-based user profiling methods that are based on both positive and negative preferences. ]]>
User profiling is a fundamental component of any personalization applications. Most existing user profiling strategies are based on objects that users are interested in (i.e., positive preferences), but not the objects that users dislike (i.e., negative preferences). In this paper, we focus on search engine personalization and develop several concept-based user profiling methods that are based on both positive and negative preferences. ]]> Mon, 23 Sep 2013 02:35:44 GMT /slideshow/deriving-concept-absed-user-profile/26447768 shailajaswami9@slideshare.net(shailajaswami9) Deriving concept absed user profile shailajaswami9 User profiling is a fundamental component of any personalization applications. Most existing user profiling strategies are based on objects that users are interested in (i.e., positive preferences), but not the objects that users dislike (i.e., negative preferences). In this paper, we focus on search engine personalization and develop several concept-based user profiling methods that are based on both positive and negative preferences. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/derivingconceptabseduserprofile-130923023544-phpapp02-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> User profiling is a fundamental component of any personalization applications. Most existing user profiling strategies are based on objects that users are interested in (i.e., positive preferences), but not the objects that users dislike (i.e., negative preferences). In this paper, we focus on search engine personalization and develop several concept-based user profiling methods that are based on both positive and negative preferences.
Deriving concept absed user profile from Shailaja Swami
]]> 360 2 https://cdn.slidesharecdn.com/ss_thumbnails/derivingconceptabseduserprofile-130923023544-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds document Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Deriving concept based user profiles /slideshow/deriving-concept-based-user-profiles/26447700 derivingconcept-baseduserprofiles-130923023149-phpapp02
User profiling is a fundamental component of any personalization applications. Most existing user profiling strategies are based on objects that users are interested in (i.e., positive preferences), but not the objects that users dislike (i.e., negative preferences). In this paper, we focus on search engine personalization and develop several concept-based user profiling methods that are based on both positive and negative preferences. We evaluate the proposed methods against our previously proposed personalized query clustering method. Experimental results show that profiles which capture and utilize both of the user’s positive and negative preferences perform the best. An important result from the experiments is that profiles with negative preferences can increase the separation between similar and dissimilar queries. The separation provides a clear threshold for an agglomerative clustering algorithm to terminate and improve the overall quality of the resulting query clusters.]]>
User profiling is a fundamental component of any personalization applications. Most existing user profiling strategies are based on objects that users are interested in (i.e., positive preferences), but not the objects that users dislike (i.e., negative preferences). In this paper, we focus on search engine personalization and develop several concept-based user profiling methods that are based on both positive and negative preferences. We evaluate the proposed methods against our previously proposed personalized query clustering method. Experimental results show that profiles which capture and utilize both of the user’s positive and negative preferences perform the best. An important result from the experiments is that profiles with negative preferences can increase the separation between similar and dissimilar queries. The separation provides a clear threshold for an agglomerative clustering algorithm to terminate and improve the overall quality of the resulting query clusters.]]> Mon, 23 Sep 2013 02:31:49 GMT /slideshow/deriving-concept-based-user-profiles/26447700 shailajaswami9@slideshare.net(shailajaswami9) Deriving concept based user profiles shailajaswami9 User profiling is a fundamental component of any personalization applications. Most existing user profiling strategies are based on objects that users are interested in (i.e., positive preferences), but not the objects that users dislike (i.e., negative preferences). In this paper, we focus on search engine personalization and develop several concept-based user profiling methods that are based on both positive and negative preferences. We evaluate the proposed methods against our previously proposed personalized query clustering method. Experimental results show that profiles which capture and utilize both of the user’s positive and negative preferences perform the best. An important result from the experiments is that profiles with negative preferences can increase the separation between similar and dissimilar queries. The separation provides a clear threshold for an agglomerative clustering algorithm to terminate and improve the overall quality of the resulting query clusters. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/derivingconcept-baseduserprofiles-130923023149-phpapp02-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> User profiling is a fundamental component of any personalization applications. Most existing user profiling strategies are based on objects that users are interested in (i.e., positive preferences), but not the objects that users dislike (i.e., negative preferences). In this paper, we focus on search engine personalization and develop several concept-based user profiling methods that are based on both positive and negative preferences. We evaluate the proposed methods against our previously proposed personalized query clustering method. Experimental results show that profiles which capture and utilize both of the user’s positive and negative preferences perform the best. An important result from the experiments is that profiles with negative preferences can increase the separation between similar and dissimilar queries. The separation provides a clear threshold for an agglomerative clustering algorithm to terminate and improve the overall quality of the resulting query clusters.
Deriving concept based user profiles from Shailaja Swami
]]> 630 2 https://cdn.slidesharecdn.com/ss_thumbnails/derivingconcept-baseduserprofiles-130923023149-phpapp02-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-shailajaswami9-48x48.jpg?cb=1523638255 https://cdn.slidesharecdn.com/ss_thumbnails/projectlist-140623041940-phpapp01-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/2014-project/36186742 2014 IEEE project https://cdn.slidesharecdn.com/ss_thumbnails/derivingconceptabseduserprofile-130923023544-phpapp02-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/deriving-concept-absed-user-profile/26447768 Deriving concept absed... https://cdn.slidesharecdn.com/ss_thumbnails/derivingconcept-baseduserprofiles-130923023149-phpapp02-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/deriving-concept-based-user-profiles/26447700 Deriving concept based...