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Similarity search and mining in uncertain databases

Matthias Renz, Reynold Cheng, Hans-Peter Kriegel
2010 Proceedings of the VLDB Endowment  
There is a number of challenges in terms of collecting, modelling, representing, querying, indexing and mining uncertain data.  ...  Managing, searching and mining uncertain data has achieved much attention in the database community recently due to new sensor technologies and new ways of collecting data.  ...  This tutorial aims at providing a comprehensive view of the state-of-the-art research in probabilistic similarity search and probabilistic data mining for uncertain data.  ... 
doi:10.14778/1920841.1921066 fatcat:rqjstjk4h5fe3kzy7b462yvn3e

Classical and Probabilistic Information Retrieval Techniques: An Audit

Qaiser Abbas
2021 Lahore Garrison University research journal of computer science and information technology  
The most important information retrieval methods include the probabilistic, fuzzy set, vector space, and boolean models.  ...  In this paper, we present a survey of these models so that their working methodology and limitations are discussed.  ...  Section 2 and 3 offer a brief introduction to IR models, including Boolean, VSM and Probabilistic. In Section 4 and 5, indexing and searching techniques for these models has be discussed.  ... 
doi:10.54692/lgurjcsit.2021.0503221 fatcat:z5becjxpdvdzhabyixmx6pfjl4

Probabilistic search team weighting---some negative results

N. Fuhr, P. Muller
1987 Proceedings of the 10th annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '87  
On the other hand, models based on probabilistic indexing outperform the ranking procedures using search term weights.  ...  The effect of probabilistic search term weighting on the improvement of retrieval quality has been demonstrated in various experiments described in the literature.  ...  In a second series of experiments, models based on probabilistic indexing (that is, document term weighting) are tested and the results are compared with those of the search term weighting models.  ... 
doi:10.1145/42005.42007 dblp:conf/sigir/FuhrM87 fatcat:5om5aldbm5bvxkl4npmlw5hpke

Interpretable Encrypted Searchable Neural Networks [article]

Kai Chen and Zhongrui Lin and Jian Wan and Chungen Xu
2019 arXiv   pre-print
In IESNN, probabilistic learning is used to obtain search ranking for searchable index, and probabilistic query is performed based on ciphertext index, which reduces the computational complexity of query  ...  In cloud security, traditional searchable encryption (SE) requires high computation and communication overhead for dynamic search and update.  ...  NJUST graduate Scientific Research Training of 'Hundred, Thousand and Ten Thousand' Project "Research on Intelligent Searchable Encryption Technology".  ... 
arXiv:1908.04998v1 fatcat:4minzjvqwjciddqpgmznhpzime

Looking back: On relevance, probabilistic indexing and information retrieval

Paul Thompson
2008 Information Processing & Management  
Forty-eight years ago Maron and Kuhns published their paper, "On Relevance, Probabilistic Indexing and Information Retrieval" (1960).  ...  This paper describes the Maron and Kuhns article and the influence that it has had on the field of information retrieval.  ...  Good, and R. Solomonoff for their comments on the state of information retrieval research around 1960. The author also thanks the two anonymous reviewers whose comments helped improve the paper.  ... 
doi:10.1016/j.ipm.2007.10.002 fatcat:ijfndl2zhnbjvkmkwbz3uxic4e

A probabilistic automated tagger to identify human-related publications

Aaron M Cohen, Zackary O Dunivin, Neil R Smalheiser
2018 Database: The Journal of Biological Databases and Curation  
However, newly published MEDLINE articles may take months to be indexed and non-MEDLINE articles lack consistent, transparent indexing of this feature.  ...  A probabilistic automated tagger to identify human-related publications. Abstract The Medical Subject Heading 'Humans' is manually curated and indicates human-related studies within MEDLINE.  ...  Acknowledgements The authors wish to acknowledge Gary Bonifield and Prerna Das for computational and programming support of this work.  ... 
doi:10.1093/database/bay079 pmid:30184195 pmcid:PMC6146117 fatcat:dfseysbpuvbtxakj4plhtkbwqm

SkipBlock: Self-indexing for Block-Based Inverted List [chapter]

Stéphane Campinas, Renaud Delbru, Giovanni Tummarello
2011 Lecture Notes in Computer Science  
Based on a cost model, we show that it is possible to achieve significant improvements on both search performance and structure's space storage.  ...  In large web search engines the performance of Information Retrieval systems is a key issue.  ...  Conclusion and future work We presented SkipBlock, a self-indexing model for block-based inverted lists.  ... 
doi:10.1007/978-3-642-20161-5_55 fatcat:kb4z7ye325eazgft7ucjslhgzy

Page 57 of Library & Information Science Abstracts Vol. , Issue 7 [page]

1995 Library & Information Science Abstracts  
space, and conventional probabilistic models.  ...  The Okapi system has been used in a series of experiments on the TREC collections, gy probabilistic models, relevance feedback, and query expansion, and interaction issues.  ... 

Cheshire II: Designing a next-generation online catalog

Ray R. Larson, Jerome McDonough, Paul O'Leary, Lucy Kuntz, Ralph Moon
1996 Journal of the American Society for Information Science  
The system uses a client-server architecture with X window client communication with an SGML-based probabilistic search engine using the 239.50 information retrieval protocol.  ...  It is based on a number of national and international standards for data description, communication, and interface technology.  ...  We plan to publish further descriptions of our findings on retrieval algorithms, use of SGML structured documents as database objects, user interfaces, and user reactions to the Cheshire II advanced online  ... 
doi:10.1002/(sici)1097-4571(199607)47:7<555::aid-asi7>;2-t fatcat:oux75vpq5jb5rhtryz7dvgao3a

A comparative study on the Assortment of Information Retrieval systems

L. Senthilvadivu
2018 International Journal of Scientific Research in Computer Sciences and Engineering  
This paper presents a brief overview of the comparisons of the few assortments of Information Retrieval (IR) models and the description of the connoisseur in the field.  ...  For thousands of years people have realized the importance of archiving and finding information.  ...  Latent semantic indexing (LSI) and concept indexing (CI) are information retrieval techniques embedded in the vector space model, which address the problem of synonymy and polysemy.  ... 
doi:10.26438/ijsrcse/v6i2.109112 fatcat:5du75zj3ezh3rlzq5dgbgtufhu


Norbert Fuhr, Norbert Gövert, Thomas Rölleke
1998 Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '98  
We describe the design and implementation of a system for logic-based multimedia retrieval.  ...  As highlevel logic for retrieval of hypermedia documents, we have developed a probabilistic object-oriented logic (POOL) which supports aggregated objects, different kinds of propositions (terms, classifications  ...  index-structure for direct search of the corresponding document numbers and probabilities.  ... 
doi:10.1145/290941.291005 dblp:conf/sigir/FuhrGR98 fatcat:geg4kpqmw5eaje3xf2am25535u

A Survey of Information Retrieval Techniques

Mang'are Fridah Nyamisa
2017 Advances in Networks  
The major information retrieval mechanisms commonly employed include vector space model, Boolean model, Fuzzy Set model, and probabilistic retrieval model.  ...  In this paper, a survey of these models is provided in order to understand their working mechanisms and shortcomings.  ...  index term and freedom of supposition for the index term; generally, the idea of probabilistic model is within a probabilistic scope, which allows the user to retrieve and which documents are relevant  ... 
doi:10.11648/ fatcat:i3ahtt53bfd2rcc5aytt6jvb6e

A Novel Trip Planner Using Effective Indexing Structure

M.K Chandrasekharan, S Shiva Shankar
2015 International Journal of Innovative Research in Computer and Communication Engineering  
Besides, we outline a pre computation method in view of the expense model and develop a list structure over the pre computed information to empower the pruning by means of the file.  ...  To handle the proficiency issue, we display the pruning systems time interim pruning and probabilistic pruning to viably discount bogus alerts of trek arrangements.  ...  To represent such a spatial road network, we use the (timedependent) probabilistic model to capture the uncertainty of its traffic data, and formulate a probabilistic timedependent graph (PT-Graph) with  ... 
doi:10.15680/ijircce.2015.0305045 fatcat:i6gxoo7k4rb5lhyjzbqyhwzrry

A survey in traditional information retrieval models

Hai Dong, Farookh Khadeer Hussain, Elizabeth Chang
2008 2008 2nd IEEE International Conference on Digital Ecosystems and Technologies  
Index Terms-index-term based information retrieval models, Boolean models, algebraic models, probabilistic models.  ...  As a matter of fact, many so-called semantic search algorithms are derived from the traditional indexterm-based search models.  ...  SEMANTIC SEARCH MODELS The traditional information retrieval models, as in Fig.1 , can be primarily divided into the category of set theoretic models, algebraic models and probabilistic models.  ... 
doi:10.1109/dest.2008.4635214 fatcat:azzki4wfq5drbk7p2yds63a2vi

A Survey on Automatic Semantic Subject Indexing of Documents using Big Data Analytics

K. Swanthana
2018 International Journal for Research in Applied Science and Engineering Technology  
The aim is to explore methods of indexing and retrieving the documents based on the different query search types, by utilizing some of the subject indexing strategy for Big Data manageability by identifying  ...  The existing strategies like, Vector Space Models, Latent Semantic Analysis, Probabilistic Latent Semantic Analysis, Logistic Regression, Linear Discriminant Analysis, Naïve Bayes and Logistic Regression  ...  Probabilistic Latent Semantic Analysis (PLSA): Probabilistic Latent Semantic Indexing is a novel approach to automated document indexing which is based on a statistical latent class model for factor analysis  ... 
doi:10.22214/ijraset.2018.4282 fatcat:mki2fowtfff4jfug2mlcnkypdi
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