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Lazy Factored Inference for Functional Probabilistic Programming
[article]
2015
arXiv
pre-print
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LFI expands the model to a bounded depth and uses the structure of the program to precisely quantify the effect of the unexpanded part of the model, producing lower and upper bounds to the probability ...
of the query. ...
INTRODUCTION Probabilistic models are growing in their richness and diversity. One of the challenges to using probabilistic models is the need to create representations and reasoning algorithms. ...
arXiv:1509.03564v1
fatcat:gimrmqbi75gvdneidw2dskg35e
Structured queries, language modeling, and relevance modeling in cross-language information retrieval
2005
Information Processing & Management
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We pursue two additional issues inherent in the comparison of structured query processing with language modeling. ...
On the other hand, when queries are expanded, language modeling gives better results, but only when using a probabilistic dictionary derived from a parallel corpus. ...
Retrieval Models and Structured Query Translation The first probabilistic retrieval model was published by Maron and Kuhns (1960) . ...
doi:10.1016/j.ipm.2004.06.008
fatcat:b7phj2x7jfbtjkef7rj3gama6m
The TopX DB&IR engine
2007
Proceedings of the 2007 ACM SIGMOD international conference on Management of data - SIGMOD '07
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This paper proposes a demo of the TopX search engine, an extensive framework for unified indexing, querying, and ranking of large collections of unstructured, semistructured, and structured data. ...
TopX integrates efficient algorithms for top-k-style ranked retrieval with powerful scoring models for text and XML documents, as well as dynamic and selftuning query expansion based on background ontologies ...
For efficient testing of structural conditions, TopX first transitively expands all structural dependencies of the query. ...
doi:10.1145/1247480.1247635
dblp:conf/sigmod/TheobaldSW07
fatcat:ehiibvqfarh3rkyilvcnmsjr3i
An Intelligent Search Engine for Agricultural Disease Prescription
[chapter]
2014
IFIP Advances in Information and Communication Technology
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In order to improve the performance of search for prescription documents, we exploit the domain-specific characteristics embedded in agricultural disease prescription, and propose a domainspecific query ...
In this paper, we focus on the domain of agriculture and develop a novel search engine specifically for agricultural disease prescription retrieval. ...
The proposed retrieval model includes modeling structure information embedded in prescription documents, structurally expanding user's query and a structural retrieval function. ...
doi:10.1007/978-3-642-54341-8_49
fatcat:wehjwu3trjaqbmc326drrauo6a
Phrase recognition and expansion for short, precision-biased queries based on a query log
1999
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '99
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In this paper we examine the question of query parsing for World Wide Web queries and present a novel method for phrase recognition and expansion. ...
We use the PCFG to compute the most probable parse for a user query, re ecting linguistic structure and word usage of the domain being parsed. ...
Acknowledgments We w ould like to thank Mats Rooth, Glenn Carroll, Franz Beil, Detlef Prescher and the Gramotron project at the University of Stuttgart for their support in the development o f the query ...
doi:10.1145/312624.312669
dblp:conf/sigir/LimaP99
fatcat:e6t6vrspeneord7xcm7luoicvq
A deductive data model for query expansion
1996
Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '96
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Each expression has one or more matchmg models at the occurrence level. The models specify the matching of the expression in database Indices built in varying ways. ...
We present a deductive data model for conceptbased query expansion. It ]s based on three abstraction levels: the conceptual, linguistic and occurrence levels. ...
In the narrower concept expanded queries, narrower concepts were first added and then the matching models for their synonymous expressions were used as above in query constrrrction. ...
doi:10.1145/243199.248146
dblp:conf/sigir/JarvelinKNSK96
fatcat:7h75n74kefdllp7hpizt2fq7ke
10 Years of Probabilistic Querying – What Next?
[chapter]
2013
Lecture Notes in Computer Science
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While probabilistic databases have focused on describing tractable query classes based on the structure of query plans and data lineage, probabilistic programming has contributed sophisticated inference ...
Over the past decade, the two research areas of probabilistic databases and probabilistic programming have intensively studied the problem of making structured probabilistic inference scalable, but-so ...
Lineage formulas are derived from a top-down grounding algorithm of queries in Datalog, which incrementally expands the query literals against the views and the extensional relations until the top-k query ...
doi:10.1007/978-3-642-40683-6_1
fatcat:lofuquzqgbb4hcjtjeqydyakbe
ArchimedesOne
2016
Proceedings of the VLDB Endowment
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Knowledge bases are becoming increasingly important in structuring and representing information from the web. ...
by applying inference rules in batches using relational operations and query-driven inference by focusing computation on the query facts. ...
Alin Dobra for the helpful discussions on query optimization. ...
doi:10.14778/3007263.3007284
fatcat:txierprif5e7djvqorulut6m3e
PROBABILISTIC MATCHSIMILARITY MEASURE FOR DOCUMENT CLUSTERING
2015
International Journal on Information Sciences and Computing
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In this paper, we develop a Probabilistic match similarity measure that naturally extends the recently proposed Web-based kernel function which are trained and tested to cluster the documents effectively ...
This method works well for Web tasks such as query/keyword matching and search query suggestion that rely heavily on the quality of similarity measures between short text segments. ...
In order to improve recall, we must make use of the expanded text representations as shown in Fig.1 . To do so, we use the language modeling framework to model query and candidate texts. ...
doi:10.18000/ijisac.50156
fatcat:xrqca6esajdh7lijxa3ihdwnfi
Using Probabilistic Topic Models in Enterprise Social Software
[chapter]
2010
Lecture Notes in Business Information Processing
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We employ Latent Dirichlet Allocation in order to elicit latent topics and use the latter to assess similarities in resource and tag recommendation as well as for the expansion of query results. ...
A challenge in these systems is to discover, organize and manage the knowledge model of topics found within the enterprise. ...
Research reported in this paper has been partially financed by the European Commission in the OrganiK project (FP7: Research for the Benefit of SMEs, 222225). ...
doi:10.1007/978-3-642-12814-1_3
fatcat:xp64upkfqjdj5m475454afdu3y
A History of Probabilistic Inductive Logic Programming
2014
Frontiers in Robotics and AI
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In Probabilistic ILP (PILP), two problems are considered: learning the parameters of a program given the structure (the rules) and learning both the structure and the parameters. ...
Usually, structure learning systems use parameter learning as a subroutine. In this article, we present an overview of PILP and discuss the main results. ...
In the first, we are given the structure (the rules) of P and we just want to infer the parameters of P, while in the second we want to infer both the structure and the parameters of P. ...
doi:10.3389/frobt.2014.00006
fatcat:tirvvcv76faq3a6v7a6cdrierq
An Ontology Based Information Retrieval System
2020
International journal of recent technology and engineering
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We propose a system that matches the query terms in the ontology/schema graph and exploits the surrounding knowledge to derive an enhanced query. ...
In this system, a user enters a query from which the meaningful concepts are extracted; using these concepts and domain ontology, query expansion is performed. ...
Probabilistic Models Classic probabilistic models also known as binary independence retrieval model, was introduced by Roberston and Spark Jones. ...
doi:10.35940/ijrte.b3781.079220
fatcat:euxmzomg75hqxj4tkox6mvusji
Automated scientific document retrieval
2010
2010 The 2nd International Conference on Computer and Automation Engineering (ICCAE)
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Probabilistic Model The Probabilistic Model introduced by Robertson and Sparck Jones is based on the assumption that terms occur independently of each other in the documents. ...
To understand the behavior of probabilistic retrieval models with respect to complexity of text document indexing; and to refine and use the models accordingly. ...
doi:10.1109/iccae.2010.5451344
fatcat:zblzowcryjcalkgxc5hol7dlfq
Category-Based Query Modeling for Entity Search
[chapter]
2010
Lecture Notes in Computer Science
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We propose a general probabilistic framework for entity search to evaluate and provide insight in the many ways of using these types of input for query modeling. ...
Users often search for entities instead of documents and in this setting are willing to provide extra input, in addition to a query, such as category information and example entities. ...
Estimating and Expanding Query Models In this section we introduce methods for estimating and expanding query models: Steps I and V in Figure 1 . ...
doi:10.1007/978-3-642-12275-0_29
fatcat:kg4paa2hzbblfgof7hdi5skxwa
Evaluation of an inference network-based retrieval model
1991
ACM Transactions on Information Systems
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The use of inference networks to support document retrieval is introduced. A network-based retrieval model is described and compared to conventional probabilistic and Boolean models. ...
The performance of a retrieval system based on the inference network model is evaluated and compared to performance with conventional retrieval models, ...
Performance
improvements
appear to arise because the Boolean queries capture structural
information
in the queries (phrase structure,
compound
nominals,
and nega-
tion) that is not exploited ...
doi:10.1145/125187.125188
fatcat:byqcaa2zljcjdflsliz2smsi7a
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