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Random walk term weighting for information retrieval
2007
Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '07
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We present a way of estimating term weights for Information Retrieval (IR), using term co-occurrence as a measure of dependency between terms. ...
Evaluation on two TREC collections and 350 topics shows that the random walk-based term weights perform at least comparably to the traditional tf·idf term weighting, while they outperform it when the distance ...
CONCLUSIONS We used a graph-based ranking model for text processing, namely the TextRank random walk algorithm, to derive term weights for Information Retrieval. ...
doi:10.1145/1277741.1277930
dblp:conf/sigir/BlancoL07
fatcat:5uolqrtyane27dw6lpoemf25ra
Query expansion using random walk models
2005
Proceedings of the 14th ACM international conference on Information and knowledge management - CIKM '05
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It has long been recognized that capturing term relationships is an important aspect of information retrieval. ...
Statistically significant differences in accuracy were observed depending on the weighting of evidence in the random walk. ...
The authors thank the anonymous reviewers for their comments. This work supported by U.S. Dept. of Education grant R305G03123. ...
doi:10.1145/1099554.1099727
dblp:conf/cikm/Collins-ThompsonC05
fatcat:o6e2xvk2c5antm7ceprze36qpm
Blog distillation using random walks
2009
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval - SIGIR '09
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We model the blogosphere as a single graph that includes extra information besides the content of the posts. By performing a random walk on this graph we extract most relevant blogs for each query. ...
By performing a random walk in this graph, we extract the most relevant blogs for a specific query. ...
We used the Terrier Information Retrieval system [6] to index the collection and retrieve documents. For each query we select the top 15000 posts by . ...
doi:10.1145/1571941.1572054
dblp:conf/sigir/KeikhaCC09
fatcat:hbgq4tlerngppnqwzgeabuhg44
Adaptive image retrieval using a Graph model for semantic feature integration
2006
Proceedings of the 8th ACM international workshop on Multimedia information retrieval - MIR '06
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Querying in this model is implemented using the theory of random walks. In addition, we present ideas to implement short-term learning from relevance feedback. ...
In this paper we present a retrieval model and learning framework for the purpose of interactive information retrieval. ...
The research leading to this paper was supported by the European Commission under contract FP6-027026, Knowledge Space of semantic inference for automatic annotation and retrieval of multimedia content-K-Space ...
doi:10.1145/1178677.1178696
dblp:conf/mir/UrbanJ06
fatcat:xnuwqg567zgrdldtqolutfw6qa
Hypergraph-of-entity
2019
Open Computer Science
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We present the hypergraph-of-entity as the next step in the graph-of-entity model, where we explore a ranking approach based on biased random walks. ...
We have previously proposed the graph-of-entity as a purely graph-based representation and retrieval model, however this model would scale poorly. ...
We would like to thank our colleagues at FEUP InfoLab, João Rocha for suggesting a switch to memorybased representations and Joana Rodrigues for patiently listening to rambles about hypergraphs. ...
doi:10.1515/comp-2019-0006
fatcat:lk66dhkm5zd2dn223t3pelrsqe
Fatigued Random Walks in Hypergraphs: A Neuronal Analogy to Improve Retrieval Performance
[article]
2021
arXiv
pre-print
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For a higher effectiveness, a higher number of random walks is usually required, which often results in lower efficiency. ...
Inspired by von Neumann and the neuron in the brain, we propose and study the usage of node and hyperedge fatigue as a way to temporarily constrict random walks during keyword-based ad hoc retrieval. ...
random walk based approach. ...
arXiv:2104.05364v1
fatcat:baektepzqzhz5lapipovbplgdu
REGIMvid at ImageCLEF2012: Concept-based Query Refinement and Relevance-based Ranking Enhancement for Image Retrieval
2012
Conference and Labs of the Evaluation Forum
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Second, we try to achieve a high-quality relevance-based result not only with choosing an adequate similarity measure but also with enhancing obtained scores by elaborating a random walk with restart, ...
In this paper, we present our proposed approach that deals with two important steps in the retrieval process, which are query analysis and relevance-based ranking. ...
Therefore, elaborating a random walk [8] is an attempt for enhancing results. ...
dblp:conf/clef/FakhfakhFKAA12
fatcat:dgiyuqpzvjdb5bqsf22w4jxjp4
Human memory search as a random walk in a semantic network
2012
Neural Information Processing Systems
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We demonstrate that the results that were taken as evidence for this account also emerge from a random walk on a semantic network, much like the random web surfer model used in internet search engines. ...
The human mind has a remarkable ability to store a vast amount of information in memory, and an even more remarkable ability to retrieve these experiences when needed. ...
In addition to being simple, random walks on semantic networks have an interesting connection to methods used for information retrieval. ...
dblp:conf/nips/AbbottAG12
fatcat:i2uvjmz2gndchiympprgnijpca
Fast query execution for retrieval models based on path-constrained random walks
2010
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '10
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The PCRW based method significantly outperformed unsupervised random walk based queries, and models with learned edge weights. Unfortunately, PCRW query systems are expensive to evaluate. ...
Many recommendation and retrieval tasks can be represented as proximity queries on a labeled directed graph, with typed nodes representing documents, terms, and metadata, and labeled edges representing ...
One very common and successful set of proximity measures are based on random walks on graphs, for instance lazy random walks [19] or personalized PageRank [6, 8] or Random Walk with Restart [25] . ...
doi:10.1145/1835804.1835916
dblp:conf/kdd/LaoC10
fatcat:ygn2mmh3tnbancpoz4pd6qruxi
Multi-modal Image Retrieval with Random Walk on Multi-layer Graphs
2016
2016 IEEE International Symposium on Multimedia (ISM)
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We therefore propose a new image retrieval solution that is able to sort images through a random walk on a multi-layer graph, where each layer corresponds to a different type of information about the image ...
We study in depth the design of the image graph and propose in particular an effective method to select the edge weights for the multi-layer graph, such that the image ranking scores are optimised. ...
Using this structure, we preserve important information about each type of information. Second, we develop a random walk process on the graph to retrieve similarity information between images. ...
doi:10.1109/ism.2016.0011
dblp:conf/ism/KhasanovaDF16
fatcat:w273bps7abcffnusdptdd3mevy
Linguistic aggregation methods in blog retrieval
2012
Information Processing & Management
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We show that using only highly relevant evidence (posts) for each blog can result in an effective retrieval system. ...
We model each post as evidence of the relevance of a blog to the query, and use aggregation methods like Ordered Weighted Averaging (OWA) operators to combine the evidence. ...
Acknowledgment We thank Mark Carman for his helps and constructive discussions. We also want to thank Amirhossein Malekpour for his great review and comments. ...
doi:10.1016/j.ipm.2011.02.001
fatcat:udji4slxkvdinewe7lx4onahvy
Random Walk-Based Semantic Annotation for On-demand Printing Products
2019
American Journal of Neural Networks and Applications
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By random walks, terms with the highest convergence probability in each product document are selected as the most relevant feature terms of the product. ...
Secondly, ProRWR builds square matrix using the TF-IDF weight matrix, rewrite the equation of random walk, and use the normalized square matrix as the input of rewrite ProRWR algorithm. ...
Product-Term Weight Computation TF-IDF is a statistical method and a commonly used term weighting method for information retrieval, which usually used to specify the term weight of a class of documents ...
doi:10.11648/j.ajnna.20190501.15
fatcat:uu2eszeyizblbl6cpkqwxk5cbq
CWI at TREC 2011: Session, Web, and Medical
2011
Text Retrieval Conference
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In addition, we studied the use of random walks on query graphs for formulating session history as search queries, but results are inconclusive. ...
In the medical track, we found that the use of medical background resources for query expansion leads to small improvements in retrieval performance. ...
We find that for different Qs the retrieved number of related queries varies (random walks for some queries result in very small local graphs compared to others), and we expect that some queries have more ...
dblp:conf/trec/HeHBVC11
fatcat:hbumk3r4kjevtdhmacmrt6tcsi
Query expansion using path-constrained random walks
2013
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval - SIGIR '13
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, and the probability of picking an expansion term for an input query is computed by a learned combination of constrained random walks on the graph. ...
This paper exploits Web search logs for query expansion (QE) by presenting a new QE method based on path-constrained random walks (PCRW), where the search logs are represented as a labeled, directed graph ...
QE is a long-standing research topic in information retrieval (IR). ...
doi:10.1145/2484028.2484058
dblp:conf/sigir/GaoXX13
fatcat:tizvpq6w4beltp5d2lfowht2xa
Ranking Entities Using Web Search Query Logs
[chapter]
2010
Lecture Notes in Computer Science
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Searching for entities is an emerging task in Information Retrieval for which the goal is finding well defined entities instead of documents matching the query terms. ...
We use Markov random walks on (1) Click Graphs -built from clickthrough data -and on (2) Session Graphs -built from user session information. ...
In order to utilize this information source for improving ER we perform a Markov random walk on the graphs. ...
doi:10.1007/978-3-642-15464-5_28
fatcat:awqjas7azrcovanarwwlim36zq
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