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Effects of Usage-Based Feedback on Video Retrieval
2011
ACM Transactions on Information Systems
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We propose a graph-based model for all types of implicit and explicit feedback, in which the relevant usage information is represented. ...
An evaluation strategy is proposed based on simulated user actions, which enables the evaluation of our recommendation strategies over a usage information pool obtained from 24 users performing four different ...
to evaluate each recommendation strategy. ...
doi:10.1145/1961209.1961214
fatcat:lshdfvddxvac7mjcnymjsby7dq
Adaptive multiple feedback strategies for interactive video search
2008
Proceedings of the 2008 international conference on Content-based image and video retrieval - CIVR '08
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In this paper, we propose adaptive multiple feedback strategies for interactive video retrieval. ...
To cater to the large number of novice users (non-expert users), an adaptive option is built-in to learn the expert user behavior so as to provide recommendations on the next feedback strategy, leading ...
In general, it is not enough to utilize only one single feedback technique to tackle different types of queries and for different video domains. ...
doi:10.1145/1386352.1386411
dblp:conf/civr/LuanZNZLC08
fatcat:vs45pml57nc7lk2aufxpywcbyu
Search trails using user feedback to improve video search
2008
Proceeding of the 16th ACM international conference on Multimedia - MM '08
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This feedback is the basis for providing recommendations to users of our video retrieval system. ...
We use community based feedback mined from the interactions of previous users of our video search system to aid users in their search tasks. ...
In particular, these techniques could be extended with other types of querying, e.g. query by example, to provide even more improved query results for users. ...
doi:10.1145/1459359.1459405
dblp:conf/mm/HopfgartnerVHJ08
fatcat:qzc64vui5fa33flxt2hw5ssi3y
Adaptive website recommendations with AWESOME
2005
The VLDB journal
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In particular, we investigate two-step selection approaches that first determine the most promising recommenders and then apply their recommendations for the current situation. ...
Furthermore, we propose and evaluate several rule-based schemes for dynamically selecting the most promising recommendations. ...
Acknowledgements We thank Robert Lokaiczyk for his help with the implementation. ...
doi:10.1007/s00778-005-0160-x
fatcat:u4eaiirmfvautow2ug3sncsobm
Community based feedback techniques to improve video search
2008
Signal, Image and Video Processing
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We use a graph based model based on implicit feedback mined from the interactions of previous users of our video search system to provide recommendations to aid users in their search tasks. ...
In particular we wish to make the challenging task of video search much easier for users. ...
As part of this work a number of different weighting schemes were evaluated in order to determine which weighting scheme was the most effective for implicit feedback for interactive video search. ...
doi:10.1007/s11760-008-0087-y
fatcat:ydlqun6mjvhdrebeetmijwglku
Preference based feedback for collaborative image retrieval
2011
Proceedings of the 3rd international workshop on Collaborative information retrieval - CIR '11
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We describe initial implementations of this approach and some evaluations of this paradigm for image search. ...
There are a many of image related search tasks that can be collaborative in nature and require input from more than one person e.g. organisation of photographs or videos from multiple views, students working ...
In an attempt to address this issue the comparison-based recommendation work of McGinty and Smyth [12] propose a number of query revision strategies that are designed to revise the current query/recommendation ...
doi:10.1145/2064075.2064082
fatcat:4bq7ilukvffndompa724ob4y5q
EGO: A personalized multimedia management and retrieval tool
2006
International Journal of Intelligent Systems
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The recommendation algorithm is described, which is based on relevance feedback techniques. ...
In this article, we sketch the development of CBIR interfaces and introduce our view on how to solve some of the problems these interfaces present. ...
It allows for different views of the results based on the features supported. ...
doi:10.1002/int.20157
fatcat:3delftfrufhsjkdszfmbfuyw64
A Large-Scale Rich Context Query and Recommendation Dataset in Online Knowledge-Sharing
[article]
2021
arXiv
pre-print
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To the best of our knowledge, this is the largest real-world interaction dataset for personalized recommendation. ...
Multiple experiments show the dataset can be used to evaluate algorithms in general top-N recommendation, sequential recommendation, and context-aware recommendation. ...
content and user interactions. • CC-CC [26] : This method uses the adaptive "Feature Sampling" strategy for the recommendation. ...
arXiv:2106.06467v1
fatcat:km3z66zbcrcmhppc4yjfuihiha
Which to View
2016
Proceedings of the 25th International Conference on World Wide Web - WWW '16
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In this paper, we propose the first framework for broadcast email prioritization by designing a novel active learning model that considers the collaborative filtering, implicit feedback and time sensitive ...
Despite lots of previous effort on this topic, broadcast email, an important type of email, is overlooked in previous literature. ...
Since different active learning algorithms query different sets of users for feedback, to make fair comparisons, the performance is evaluated on the same set of users, which is the intersection of the ...
doi:10.1145/2872427.2883049
dblp:conf/www/WangEBZGC16
fatcat:u6wkij7vrbfqde4viuqoocl4a4
Improving recommender systems with adaptive conversational strategies
2009
Proceedings of the 20th ACM conference on Hypertext and hypermedia - HT '09
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This strategy is optimal for the given model of the interaction and it is adapted to the users' behaviors. ...
We show that the optimal strategy is different from the fixed one, and supports more effective and efficient interaction sessions. ...
Users specify their preferences by providing during the interaction various types of information or feedbacks, which are used to update the user model, and hence inform future recommendations. ...
doi:10.1145/1557914.1557930
dblp:conf/ht/MahmoodR09
fatcat:exxkiok2xne2zcs73ngoio3hli
A Unified Relevance Feedback Framework for Web Image Retrieval
2009
IEEE Transactions on Image Processing
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To seamlessly combine textual feature-based RF and visual feature-based RF, a query concept-dependent fusion strategy is automatically learned. ...
In this paper, we propose a unified relevance feedback framework for Web image retrieval. Our framework shows advantage over traditional RF mechanisms in the following three aspects. ...
This property of the parameter results in a query concept-dependent fusion strategy for relevance feedback in both textual and visual space.
III. ...
doi:10.1109/tip.2009.2017128
pmid:19362910
fatcat:ygpc546pj5ftnbrgzsuxcillga
An implicit feedback approach for interactive information retrieval
2006
Information Processing & Management
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One reason for this is that they may have difficulty devising queries to express their information needs. ...
The approach chooses terms to better represent information needs by monitoring searcher interaction with different representations of top-ranked documents. ...
the subject groups in the type and amount of interaction). ...
doi:10.1016/j.ipm.2004.08.010
fatcat:4l7q3ycjqbfzzakfzzg4evzsw4
Toward the exploitation of social access patterns for recommendation
2007
Proceedings of the 2007 ACM conference on Recommender systems - RecSys '07
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ASSIST exploits multiple forms of social implicit feedback in order to generate well-informed user recommendations in the online information retrieval domain. ...
The online information retrieval process across different repositories shares similarities with content access facilities and user behaviors even when containing inherently different content types. ...
In this work we will refer to examples using a multimedia platform for serving up videos, YouTube (www.youtube.com) to illustrate how our recommendation strategies could be implemented in an alternative ...
doi:10.1145/1297231.1297266
dblp:conf/recsys/FreyneFC07
fatcat:36vqyaac6zeatojkhhxvwt5mru
Advances and Challenges in Conversational Recommender Systems: A Survey
[article]
2021
arXiv
pre-print
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2021 pre-print arXiv:2101.09459v3 fatcat:x6irqgc7wfcmbonymeohls3dfaOther Versions
Existing models, technologies, and evaluation methods for CRSs are far from mature. In this paper, we provide a systematic review of the techniques used in current CRSs. ...
Recommender systems exploit interaction history to estimate user preference, having been heavily used in a wide range of industry applications. ...
an explicit strategy to deal with different feedback. ...
arXiv:2101.09459v6
fatcat:j7djzhrv6fazpogmnj7r4e4f2y
TRECVID 2009 of MCG-ICT-CAS
2009
TREC Video Retrieval Evaluation
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This paper describes the highlights of our interactive search system VideoMap for TRECVID 2009. ...
Meanwhile, the system has powerful multiple modality feedback strategies, including the visual-based feedback, concept-based feedback and community-based feedback. ...
Figure 8 The performance for 24 topics of automatic multi-strategies feedback (run1)
Experiments and Analysis We submitted 10 type A runs for interactive search task. ...
dblp:conf/trecvid/CaoZFBPLGWXZM09
fatcat:dupkc3rutvgcpasjzpxwcfqui4
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