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KB-Enabled Query Recommendation for Long-Tail Queries

Zhipeng Huang, Bogdan Cautis, Reynold Cheng, Yudian Zheng
2016 Proceedings of the 25th ACM International on Conference on Information and Knowledge Management - CIKM '16  
As shown in our experiments, our approach provides better recommendation results for long-tail queries than existing solutions.  ...  Most of these solutions, which perform extensive analysis of users' search history (or query logs), are largely insufficient for long-tail queries that rarely appear in query logs.  ...  We would like to thank the reviewers for their insightful comments.  ... 
doi:10.1145/2983323.2983650 dblp:conf/cikm/HuangCCZ16 fatcat:vnf55xx7yngspfoc35ptzjyqku

When entities meet query recommender systems

Diego Ceccarelli, Sergiu Gordea, Claudio Lucchese, Franco Maria Nardini, Raffale Perego
2013 Proceedings of the 28th Annual ACM Symposium on Applied Computing - SAC '13  
In this paper, we explore the use of entities that can be extracted from a query log to enhance query recommendation.  ...  query recommendation algorithm to take into account the semantic information associated with the submitted queries.  ...  Acknowledgements We acknowledge the Europeana Foundation for providing us the query logs used in our experimentation. This work was partially supported by the EU project InGeoCLOUDS (no. 297300).  ... 
doi:10.1145/2480362.2480540 dblp:conf/sac/CeccarelliGLNP13 fatcat:jxvzhv2kqzhzxd3vhokhlamnei

Ten Years of Knowledge Harvesting: Lessons and Challenges

Gerhard Weikum, Johannes Hoffart, Fabian M. Suchanek
2016 IEEE Data Engineering Bulletin  
Automatically constructed knowledge bases -KB's for short -have become a powerful asset for search, analytics, recommendations, and data integration, with intensive use at big industrial stakeholders.  ...  For illustration, here are some examples of SPO triples about Steve Jobs:  ...  A second challenge arises from long-tail entities and long-tail classes. There are many lesser known musicians, regional politicians and good but not exactly famous scientists.  ... 
dblp:journals/debu/WeikumHS16 fatcat:3ag5kwndn5divkwjimusmsa3ia

Conclusions and Future Directions [chapter]

Krisztian Balog
2018 Advanced Topics in Information Retrieval  
Open challenges include the discovery of long tail and emerging entities, and the quality of data (correctness and trustworthiness of facts); see Sect. 10.3.3 for further data-related issues.  ...  In this regard, voice-based result presentation that enables a completely hand-free interaction with the user still has a long way to go [9] .  ... 
doi:10.1007/978-3-319-93935-3_10 fatcat:uisbfxmmh5f2ncszn6g3j3imge

RecPipe: Co-designing Models and Hardware to Jointly Optimize Recommendation Quality and Performance [article]

Udit Gupta, Samuel Hsia, Jeff Zhang, Mark Wilkening, Javin Pombra, Hsien-Hsin S. Lee, Gu-Yeon Wei, Carole-Jean Wu, David Brooks
2021 arXiv   pre-print
Deep learning recommendation systems must provide high quality, personalized content under strict tail-latency targets and high system loads.  ...  In particular, RPAccel processes queries in sub-batches to pipeline recommendation stages, implements dual static and dynamic embedding caches, a set of top-k filtering units, and a reconfigurable systolic  ...  We propose a new system, RecPipe, that enables design space exploration and optimization for multi-stage recommendation inference.  ... 
arXiv:2105.08820v2 fatcat:tsq6jygecvdo5l2bgs5pcbqbmu

Enriching network security analysis with time travel

Gregor Maier, Robin Sommer, Holger Dreger, Anja Feldmann, Vern Paxson, Fabian S hneider
2008 Proceedings of the ACM SIGCOMM 2008 conference on Data communication - SIGCOMM '08  
The TM leverages the heavy-tailed nature of network flows to capture nearly all of the likely-interesting traffic while storing only a small fraction of the total volume.  ...  We present a Time Machine (TM) for network traffic that provides such a capability.  ...  For scanners, we increase the cutoff from 15 KB to 50 KB; for all other offenders we disable the cutoff altogether.  ... 
doi:10.1145/1402958.1402980 dblp:conf/sigcomm/MaierSDFPS08 fatcat:uzsjyye2ofhfzihn6kdrctcfze

Enriching network security analysis with time travel

Gregor Maier, Robin Sommer, Holger Dreger, Anja Feldmann, Vern Paxson, Fabian S hneider
2008 Computer communication review  
The TM leverages the heavy-tailed nature of network flows to capture nearly all of the likely-interesting traffic while storing only a small fraction of the total volume.  ...  We present a Time Machine (TM) for network traffic that provides such a capability.  ...  For scanners, we increase the cutoff from 15 KB to 50 KB; for all other offenders we disable the cutoff altogether.  ... 
doi:10.1145/1402946.1402980 fatcat:vqz446q24nazpk7ps7wzxcisxe

Utilizing Entities for an Enhanced Search Experience [chapter]

Krisztian Balog
2018 Advanced Topics in Information Retrieval  
We refer to Table 9 .1 for the notation used in this chapter. Query Assistance Chapter 7 dealt with query understanding from the machine's point of view.  ...  Finally, in Sect. 9.3, we describe entity recommendation methods that present users with contextual suggestions, encourage exploration, and allow for serendipitous discoveries.  ...  Entity Types An obvious limitation of query-flow graphs is that they cannot make recommendations for long-tail or previously unseen queries. Szpektor et al.  ... 
doi:10.1007/978-3-319-93935-3_9 fatcat:omj2eork2zgq7nvm7icxmxweey

Improving Distant Supervised Relation Extraction by Dynamic Neural Network [article]

Yanjie Gou, Yinjie Lei, Lingqiao Liu, Pingping Zhang, Xi Peng
2019 arXiv   pre-print
By using this mechanism, the network can simultaneously handle the style shift problem and enhance the prediction accuracy for long-tail classes.  ...  Therefore, it can be trained cross different relation classes and further enhance those classes with few samples, i.e., long-tail classes.  ...  They both transfer the well-trained features to the long-tail classes by connecting relations according to the KB hierarchies.  ... 
arXiv:1911.06489v2 fatcat:hl4ovrxnhja55dzwk3ehjifgyi

WiscKey

Lanyue Lu, Thanumalayan Sankaranarayana Pillai, Hariharan Gopalakrishnan, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau
2017 ACM Transactions on Storage  
Microbenchmark results show that WiscKey is 2.5×-111× faster than LevelDB for loading a database and 1.6×-14× faster for random lookups.  ...  Acknowledgments We thank the anonymous reviewers and Ethan Miller (our shepherd) for their feedback.  ...  Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and may not reflect the views of NSF or other institutions.  ... 
doi:10.1145/3033273 fatcat:ylsdbtcl3vhvfoxtknludhny2i

Smart Selection

Patrick Pantel, Michael Gamon, Ariel Fuxman
2014 Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)  
There is a need for a new text selection paradigm that goes beyond the high acuity selection-by-mouse that we have relied on for decades.  ...  Natural touch interfaces, common now in devices such as tablets and smartphones, make it cumbersome for users to select text.  ...  Acknowledgments The authors thank Aitao Chen for sharing his NER tagger for our experiments, and Bernhard Kohlmeier, Pradeep Chilakamarri, Ashok Chandra, David Hamilton, and Bo Zhao for their guidance  ... 
doi:10.3115/v1/p14-1143 dblp:conf/acl/PantelGF14 fatcat:xoabwrcjlngbnmi57ui6n3jnm4

Context-Aware Explainable Recommendation Based on Domain Knowledge Graph

Muzamil Hussain Syed, Tran Quoc Bao Huy, Sun-Tae Chung
2022 Big Data and Cognitive Computing  
Providing recommendations based on users' natural language queries is an equally difficult undertaking.  ...  In this paper, we propose a novel, context-aware recommender system, based on domain KG, to respond to user-defined natural queries. The proposed recommender system consists of three stages.  ...  Moreover, it enables deeper queries and reasoning over KG for efficient recommendations. Figure 2 shows the ontology of our restaurant domain KG.  ... 
doi:10.3390/bdcc6010011 fatcat:elimpdaw6vao5hhqm6bl5a47mi

Catch the Whole Lot in an Action: Rapid Precise Packet Loss Notification in Data Center

Peng Cheng, Fengyuan Ren, Ran Shu, Chuang Lin
2014 Symposium on Networked Systems Design and Implementation  
An increasing number of TCP performance issues including TCP Incast, TCP Outcast, and long query completion times are common in large-scale data centers.  ...  Keshav for his constructive suggestions, and acknowledge the anonymous reviewers for their valuable comments.  ...  Therefore, we recommend that the threshold for duplicate ACKs is set to a relatively large number.  ... 
dblp:conf/nsdi/ChengRSL14 fatcat:4ayxetzeirecbaoqqyu7zvylgq

RobinHood: Tail Latency Aware Caching - Dynamic Reallocation from Cache-Rich to Cache-Poor

Daniel S. Berger, Benjamin Berg, Timothy Zhu, Siddhartha Sen, Mor Harchol-Balter
2018 USENIX Symposium on Operating Systems Design and Implementation  
We also thank the anonymous reviewers, and our shepherd, Frans Kaashoek, for their feedback.  ...  Introduction Request tail latency matters. Providers of large userfacing web services have long faced the challenge of achieving low request latency.  ...  Some existing approaches for reducing tail latency rely on load balancing between servers and aim to equalize query tail latencies between servers.  ... 
dblp:conf/osdi/BergerBZ0H18 fatcat:vhng3oi4nbf5bgzoqcbh7ymjvq

Commonsense Properties from Query Logs and Question Answering Forums [article]

Julien Romero, Simon Razniewski, Koninika Pal, Jeff Z. Pan, Archit Sakhadeo, Gerhard Weikum
2021 arXiv   pre-print
Commonsense knowledge about object properties, human behavior and general concepts is crucial for robust AI applications.  ...  This paper presents Quasimodo, a methodology and tool suite for distilling commonsense properties from non-standard web sources.  ...  We thank the anonymous reviewers and Niket Tandon for helpful comments.  ... 
arXiv:1905.10989v4 fatcat:h2iuxuc7nvfudkycgvbqx5kxqy
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