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short-paper

Using program synthesis for social recommendations

Authors:

Armando Solar-Lezama,

Samuel MaddenAuthors Info & Claims

CIKM '12: Proceedings of the 21st ACM international conference on Information and knowledge management

Pages 1732 - 1736

https://doi.org/10.1145/2396761.2398507

Published: 29 October 2012 Publication History

Abstract

This paper presents a new approach to select events of interest to users in a social media setting where events are generated from mobile devices. We argue that the problem is best solved by inductive learning, where the goal is to first generalize from the users' expressed "likes" and "dislikes" of specific events, then to produce a program that can be used to collect only data of interest.

The key contribution of this paper is a new algorithm that combines machine learning techniques with program synthesis technology to learn users' preferences. We show that when compared with the more standard approaches, our new algorithm provides up to order-of-magnitude reductions in model training time, and significantly higher prediction accuracies for our target application.¹

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Cited By

Cao YXie XHuang K(2023)Learn to Explore: on Bootstrapping Interactive Data Exploration with Meta-learning2023 IEEE 39th International Conference on Data Engineering (ICDE)10.1109/ICDE55515.2023.00135(1720-1733)Online publication date: Apr-2023
https://doi.org/10.1109/ICDE55515.2023.00135
Huang EDiao YLiu APeng LPalma L(2023)Efficient and robust active learning methods for interactive database explorationThe VLDB Journal10.1007/s00778-023-00816-x33:4(931-956)Online publication date: 16-Nov-2023
https://doi.org/10.1007/s00778-023-00816-x
Bragg NFoster JRoux CSolar-Lezama A(2021)Program Sketching by Automatically Generating Mocks from TestsComputer Aided Verification10.1007/978-3-030-81685-8_38(808-831)Online publication date: 15-Jul-2021
https://doi.org/10.1007/978-3-030-81685-8_38
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Index Terms

Using program synthesis for social recommendations
1. Information systems
  1. Information systems applications
    1. Data mining

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Published In

cover image ACM Conferences

CIKM '12: Proceedings of the 21st ACM international conference on Information and knowledge management

October 2012

2840 pages

ISBN:9781450311564

DOI:10.1145/2396761

General Chair:
Xuewen Chen
Wayne State University, USA
,
Program Chairs:
Guy Lebanon
Georgia Institute of Technology
,
Haixun Wang
Microsoft Research Asia
,
Mohammed J. Zaki
Rensselaer Polytechnic Institute

Copyright © 2012 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 29 October 2012

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CIKM'12

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CIKM'12: 21st ACM International Conference on Information and Knowledge Management

October 29 - November 2, 2012

Hawaii, Maui, USA

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Overall Acceptance Rate 1,861 of 8,427 submissions, 22%

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Cited By

Cao YXie XHuang K(2023)Learn to Explore: on Bootstrapping Interactive Data Exploration with Meta-learning2023 IEEE 39th International Conference on Data Engineering (ICDE)10.1109/ICDE55515.2023.00135(1720-1733)Online publication date: Apr-2023
https://doi.org/10.1109/ICDE55515.2023.00135
Huang EDiao YLiu APeng LPalma L(2023)Efficient and robust active learning methods for interactive database explorationThe VLDB Journal10.1007/s00778-023-00816-x33:4(931-956)Online publication date: 16-Nov-2023
https://doi.org/10.1007/s00778-023-00816-x
Bragg NFoster JRoux CSolar-Lezama A(2021)Program Sketching by Automatically Generating Mocks from TestsComputer Aided Verification10.1007/978-3-030-81685-8_38(808-831)Online publication date: 15-Jul-2021
https://doi.org/10.1007/978-3-030-81685-8_38
Shi LLi YLoo BAlur R(2021)Network Traffic Classification by Program SynthesisTools and Algorithms for the Construction and Analysis of Systems10.1007/978-3-030-72016-2_23(430-448)Online publication date: 20-Mar-2021
https://doi.org/10.1007/978-3-030-72016-2_23
Mariano BReese JXu SNguyen TQiu XFoster JSolar-Lezama A(2019)Program synthesis with algebraic library specificationsProceedings of the ACM on Programming Languages10.1145/33605583:OOPSLA(1-25)Online publication date: 10-Oct-2019
https://dl.acm.org/doi/10.1145/3360558
Huang EPeng LPalma LAbdelkafi ALiu ADiao Y(2018)Optimization for active learning-based interactive database explorationProceedings of the VLDB Endowment10.14778/3275536.327554212:1(71-84)Online publication date: 1-Sep-2018
https://dl.acm.org/doi/10.14778/3275536.3275542
Wang XDillig ISingh R(2017)Program synthesis using abstraction refinementProceedings of the ACM on Programming Languages10.1145/31581512:POPL(1-30)Online publication date: 27-Dec-2017
https://dl.acm.org/doi/10.1145/3158151
Wang CCheung ABodik R(2017)Synthesizing highly expressive SQL queries from input-output examplesACM SIGPLAN Notices10.1145/3140587.306236552:6(452-466)Online publication date: 14-Jun-2017
https://dl.acm.org/doi/10.1145/3140587.3062365
Wang CCheung ABodik RCohen AVechev M(2017)Synthesizing highly expressive SQL queries from input-output examplesProceedings of the 38th ACM SIGPLAN Conference on Programming Language Design and Implementation10.1145/3062341.3062365(452-466)Online publication date: 14-Jun-2017
https://dl.acm.org/doi/10.1145/3062341.3062365
Cheung ASolar-Lezama A(2016)Computer-Assisted Query FormulationFoundations and Trends in Programming Languages10.1561/25000000183:1(1-94)Online publication date: 1-Jun-2016
https://dl.acm.org/doi/10.1561/2500000018
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