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Pseudo-Query Reformulation
[article]
2015
arXiv
pre-print
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This framework allows us to test existing performance prediction methods as heuristics for the graph search process. ...
We present a general framework for automatic query reformulation based on discrete optimization. ...
For the robust and web datasets, we notice PQR significantly outperforming RM3 for high precision metrics but showing weaker performance for high recall metrics. ...
arXiv:1507.03928v1
fatcat:ouorddhafnezlm725cusovneiu
Semantic Answer Type and Relation Prediction Task (SMART 2021)
[article]
2022
arXiv
pre-print
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2021 pre-print arXiv:2112.07606v1 fatcat:dhpxrjin4vgu3fumixov3cr4om
This paper discusses the task descriptions, benchmark datasets, and evaluation metrics. For more information, please visit https://smart-task.github.io/2021/. ...
Question type and answer type prediction can play a key role in knowledge base question answering systems providing insights about the expected answer that are helpful to generate correct queries or rank ...
Relation prediction is a vital step towards formulating the correct query to extract the answer from the knowledge base. ...
arXiv:2112.07606v2
fatcat:ms7ejvanlfhqzntlj2cmpfjo74
Graph Pattern Entity Ranking Model for Knowledge Graph Completion
[article]
2019
arXiv
pre-print
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By doing so, we can find graph patterns which are useful for predicting facts. Then, we perform link prediction tasks on standard datasets to evaluate our GRank method. ...
We show that our approach outperforms other state-of-the-art approaches such as ComplEx and TorusE for standard metrics such as HITS@ n and MRR. ...
We would like to thank Patrik Schneider for helpful writing advice. ...
arXiv:1904.02856v1
fatcat:3rvnhhrb4zc47gtbukrvatr3sy
Pick Your Neighborhood – Improving Labels and Neighborhood Structure for Label Propagation
[chapter]
2011
Lecture Notes in Computer Science
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In this paper, we use metric learning to improve this critical step by increasing the precision of the nearest neighbors and building our graph in this new metric space. ...
We show that learning of neighborhood relations before constructing the graph consistently improves performance of two label propagation schemes on three different datasets -achieving the best performance ...
Conclusion In this work, we use metric learning to enhance our nearest neighborhood structure that is key for graph-based algorithms and their performance. ...
doi:10.1007/978-3-642-23123-0_16
fatcat:nussj65mhjd2hh5jlawy6ta4lu
AMUSED: A Multi-Stream Vector Representation Method for Use in Natural Dialogue
[article]
2019
arXiv
pre-print
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Current architectures only take care of semantic and contextual information for a given query and fail to completely account for syntactic and external knowledge which are crucial for generating responses ...
and syntactic information by incorporating Graph Convolution Networks (GCN) over their dependency parse. ...
Next Dialogue Prediction Task: Various components of AMUSED are analysed for their performance on next dialogue prediction task. ...
arXiv:1912.10160v1
fatcat:xhmmpnsz2fbqtexdhuhgk7p3a4
Enhanced Information Access to Social Streams Through Word Clouds with Entity Grouping
2015
Proceedings of the 11th International Conference on Web Information Systems and Technologies
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Critically, this supports MAP as a tool for predicting word cloud quality without requiring a human in the loop. ...
An extrinsic crowdsourced user evaluation of generated word clouds was performed. ...
Second, graph-based methods allow biasing of word cloud generation toward user preferences or search queries. Our graph-based selection methods firstly transforms terms space into a graph. ...
doi:10.5220/0005403101830193
dblp:conf/webist/LeginusDD15
fatcat:7at67jj37rgbbhcka3gakqogae
Information Extraction as Link Prediction: Using Curated Citation Networks to Improve Gene Detection
[chapter]
2009
Lecture Notes in Computer Science
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In this paper we explore the usefulness of various types of publication-related metadata, such as citation networks and curated databases, for the task of identifying genes in academic biomedical publications ...
Framed in this way, the problem becomes one of predicting links between authors and genes in the publication network. ...
ple way to do this would be to use that distribution as a prior for any number of probabilistic information extraction methods. ...
doi:10.1007/978-3-642-03417-6_53
pmid:21234278
pmcid:PMC3018763
fatcat:ar2xbu5bpnd7bpifsqk6fxr2pi
Facilitating prediction of adverse drug reactions by using knowledge graphs and multi-label learning models
2017
Briefings in Bioinformatics
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We present a specific way of using knowledge graphs to generate different feature sets and demonstrate favourable performance of selected off-the-shelf multi-label learning models in comparison to existing ...
The presented approach can be easily extended to other feature sources or machine learning methods, making it flexible for experiments tuned towards specific requirements of end users. ...
All data files are available for download at http://purl.com/bib-adr-prediction. Further details on the feature extraction step and manipulation of data sets are provided in the supplemental material. ...
doi:10.1093/bib/bbx099
pmid:28968655
fatcat:vt4b4nlykjd7fhfhd43r23q7lq
Towards rich query interpretation
2010
Proceedings of the 19th international conference on World wide web - WWW '10
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We formalize the notion of template as a sequence of keywords and domain attributes, and our objective is to discover templates with high precision and recall for matching queries in a domain of interest ...
We propose to mine structured query templates from search logs, for enabling rich query interpretation that recognizes both query intents and associated attributes. ...
precision as the quality metrics. ...
doi:10.1145/1772690.1772692
dblp:conf/www/AgarwalKC10
fatcat:inz7vout5jc6xi2o3jhwa7nxd4
On Search Engine Evaluation Metrics
[article]
2013
arXiv
pre-print
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Only recently, the question of the significance of individual metrics started being raised, as these metrics' correlations to real-world user experiences or performance have generally not been well-studied ...
Also, a framework for simultaneously evaluating many metrics while varying their parameters and evaluation standards is introduced. ...
He gave me the possibility to write a part of this thesis as part of my research at the Department of Information Science at Düsseldorf University; and it was also him who arranged for undergraduate students ...
arXiv:1302.2318v1
fatcat:wye4hfhvxjh27adetcccnyynyu
BenchDW
2013
Proceedings of the 28th Annual ACM Symposium on Applied Computing - SAC '13
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However, the success of systems biology is contingent on the ability to integrate a wide variety of types of biological data to automatically predict, assign functional annotations of proteins and perform ...
It currently comprises 22 different metrics ranging from documentation quality to accuracy and response times, which may be recorded for different hardware configurations. ...
Performance
2
Time to design and run the queries for a warehouse, com-
pared to the normalized database
Query-design complexity
Performance
8
Time to translate the queries from natural language ...
doi:10.1145/2480362.2480612
dblp:conf/sac/TripletB13
fatcat:ht47s2f4ybfsleejehq4xxngli
Metrics for the Prediction of Evolution Impact in ETL Ecosystems: A Case Study
2012
Journal on Data Semantics
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We focus on a set of graph-theoretic metrics for the prediction of evolution impact and we investigate their fit into real-world ETL scenarios. ...
In this paper, we focus on ways to predict the maintenance effort of ETL workflows and we explore techniques for assessing the quality of ETL designs under the prism of evolution. ...
Acknowledgments We would like to thank the anonymous reviewers of a first version of this paper for their constructive comments that improved the clarity and completeness of the paper. ...
doi:10.1007/s13740-012-0006-9
fatcat:fbbvn53ehfb2dja3ny2iexhnru
Click-boosted graph ranking for image retrieval
2017
Computer Science and Information Systems
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Towards this end, this paper propose a novel click-boosted graph ranking framework for image retrieval, which consists of two coupled components. ...
Extensive experiments for the tasks of click predicting and image ranking validate the effectiveness of the proposed methods in comparison to several existing approaches. ...
for Talents of Beijing Jiaotong University' (2015RC008). ...
doi:10.2298/csis170212020j
fatcat:ja4vi6bhqjg3fftoauvbrmg2ja
CMsearch: simultaneous exploration of protein sequence space and structure space improves not only protein homology detection but also protein structure prediction
2016
Bioinformatics
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Results: We tested CMsearch on two challenging tasks, protein homology detection and protein structure prediction, by querying all 8332 PDB40 proteins. ...
Motivation: Protein homology detection, a fundamental problem in computational biology, is an indispensable step toward predicting protein structures and understanding protein functions. ...
Jinbo Xu for fruitful discussions and valuable comments. ...
doi:10.1093/bioinformatics/btw271
pmid:27307635
pmcid:PMC4908355
fatcat:swth7pxhifhcferlebrx463wo4
A Semantic Framework for Evaluating Topical Search Methods
2011
CLEI Electronic Journal
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The use of semantic simi- larity data allows to capture the notion of partial relevance, generalizing traditional evaluation metrics, and giving rise to novel performance measures such as semantic precision ...
The evaluated systems include a baseline, a supervised version of the Bo1 query refinement method and two multi-objective evolutionary algorithms for context-based retrieval. ...
Precision. This well-known performance evaluation metric is computed as the fraction of retrieved documents which are known to be relevant to topic t: Precision(q, t) = |A q ∩ R t |/|A q |. ...
doi:10.19153/cleiej.14.1.2
fatcat:rkmqi4mexfa4hmbt4vjioqkfei
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