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Pseudo-Query Reformulation [article]

Fernando Diaz
2015 arXiv   pre-print
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]

Nandana Mihindukulasooriya, Mohnish Dubey, Alfio Gliozzo, Jens Lehmann, Axel-Cyrille Ngonga Ngomo, Ricardo Usbeck, Gaetano Rossiello, Uttam Kumar
2022 arXiv   pre-print
This paper discusses the task descriptions, benchmark datasets, and evaluation metrics. For more information, please visit  ...  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]

Takuma Ebisu, Ryutaro Ichise
2019 arXiv   pre-print
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]

Sandra Ebert, Mario Fritz, Bernt Schiele
2011 Lecture Notes in Computer Science  
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]

Gaurav Kumar, Rishabh Joshi, Jaspreet Singh, Promod Yenigalla
2019 arXiv   pre-print
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

Martin Leginus, Leon Derczynski, Peter Dolog
2015 Proceedings of the 11th International Conference on Web Information Systems and Technologies  
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]

Andrew Arnold, William W. Cohen
2009 Lecture Notes in Computer Science  
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

Emir Muñoz, Vít Nováček, Pierre-Yves Vandenbussche
2017 Briefings in Bioinformatics  
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 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

Ganesh Agarwal, Govind Kabra, Kevin Chen-Chuan Chang
2010 Proceedings of the 19th international conference on World wide web - WWW '10  
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]

Pavel Sirotkin
2013 arXiv   pre-print
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


Thomas Triplet, Gregory Butler
2013 Proceedings of the 28th Annual ACM Symposium on Applied Computing - SAC '13  
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

George Papastefanatos, Panos Vassiliadis, Alkis Simitsis, Yannis Vassiliou
2012 Journal on Data Semantics  
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

Jun Wu, Yu He, Xiaohong Qin, Na Zhao, Yingpeng Sang
2017 Computer Science and Information Systems  
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

Xuefeng Cui, Zhiwu Lu, Sheng Wang, Jim Jing-Yan Wang, Xin Gao
2016 Bioinformatics  
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

Rocío L. Cecchini, Carlos M. Lorenzetti, Ana G. Maguitman, Filippo Menczer
2011 CLEI Electronic Journal  
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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