Cited By
View all- Lagrée PCautis BVahabi H(2017)As-You-Type Social Aware SearchACM Transactions on Intelligent Systems and Technology10.1145/30359698:5(1-31)Online publication date: 30-Jun-2017
A Network-Aware Approach for Searching As-You-Type in Social Media
Pages 563 - 572
Abstract
We present in this paper a novel approach for as-you-type top-k keyword search over social media. We adopt a natural "network-aware" interpretation for information relevance, by which information produced by users who are closer to the seeker is considered more relevant. In practice, this query model poses new challenges for effectiveness and efficiency in online search, even when a complete query is given as input in one keystroke. This is mainly because it requires a joint exploration of the social space and classic IR indexes such as inverted lists. We describe a memory-efficient and incremental prefix-based retrieval algorithm, which also exhibits an anytime behavior, allowing to output the most likely answer within any chosen running-time limit. We evaluate it through extensive experiments for several applications and search scenarios, including searching for posts in micro-blogging (Twitter and Tumblr), as well as searching for businesses based on reviews in Yelp. They show that our solution is effective in answering real-time as-you-type searches over social media.
References
[1]
B. Bahmani and A. Goel. Partitioned multi-indexing: bringing order to social search. In WWW, 2012.
[2]
H. Bast, C. W. Mortensen, and I. Weber. Output-sensitive autocompletion search. Inf. Retr., 11(4):269--286, 2008.
[3]
H. Bast and I. Weber. Type less, find more: Fast autocompletion search with a succinct index. In SIGIR, 2006.
[4]
F. Cai, S. Liang, and M. de Rijke. Time-sensitive personalized query auto-completion. In CIKM, 2014.
[5]
Y. Chang, L. Tang, Y. Inagaki, and Y. Liu. What is Tumblr: A statistical overview and comparison. SIGKDD Expl., 16(1), 2014.
[6]
M. Curtiss, I. Becker, T. Bosman, S. Doroshenko, L. Grijincu, T. Jackson, S. Kunnatur, S. Lassen, P. Pronin, S. Sankar, G. Shen, G. Woss, C. Yang, and N. Zhang. Unicorn: A system for searching the social graph. VLDB, 6(11), 2013.
[7]
G. Das, D. Gunopulos, N. Koudas, and D. Tsirogiannis. Answering top-k queries using views. In VLDB, 2006.
[8]
R. Fagin, A. Lotem, and M. Naor. Optimal aggregation algorithms for middleware. In PODS, 2001.
[9]
J. Feng and G. Li. Efficient fuzzy type-ahead search in XML data. IEEE Trans. on Knowl. and Data Eng., 24(5), 2012.
[10]
W. Hon, R. Shah, and J. S. Vitter. Space-efficient framework for top-k string retrieval problems. In FOCS, 2009.
[11]
B.-J. P. Hsu and G. Ottaviano. Space-efficient data structures for top-k completion. In WWW, 2013.
[12]
S. Ji, G. Li, C. Li, and J. Feng. Efficient interactive fuzzy keyword search. In WWW, 2009.
[13]
D. Jiang, K. W.-T. Leung, J. Vosecky, and W. Ng. Personalized query suggestion with diversity awareness. In ICDE, pages 400--411, 2014.
[14]
L. Katz. Psychometrika, (1), Mar. 1953.
[15]
P. Lagrée, B. Cautis, and H. Vahabi. A network-aware approach for searching as-you-type in social media - extended version. http://arxiv.org/abs/1507.08107/, 2015.
[16]
G. Li, J. Feng, and C. Li. Supporting search-as-you-type using SQL in databases. IEEE Trans. on Knowl. and Data Eng., 25(2), 2013.
[17]
G. Li, S. Ji, C. Li, J. Wang, and J. Feng. Efficient fuzzy type-ahead search in tastier. In In ICDE, pages 1105--1108, 2010.
[18]
G. Li, J. Wang, C. Li, and J. Feng. Supporting efficient top-k queries in type-ahead search. In SIGIR, 2012.
[19]
S. Maniu and B. Cautis. Taagle: Efficient, personalized search in collaborative tagging networks. In SIGMOD, 2012.
[20]
S. Maniu and B. Cautis. Context-aware top-k processing using views. In CIKM, 2013.
[21]
S. Maniu and B. Cautis. Network-aware search in social tagging applications: Instance optimality versus efficiency. In CIKM, 2013.
[22]
Q. Mei, D. Zhou, and K. Church. Query suggestion using hitting time. In CIKM, 2008.
[23]
M. Pennacchiotti, F. Silvestri, H. Vahabi, and R. Venturini. Making your interests follow you on twitter. In CIKM, 2012.
[24]
M. Potamias, F. Bonchi, C. Castillo, and A. Gionis. Fast shortest path distance estimation in large networks. In CIKM, 2009.
[25]
R. Schenkel, T. Crecelius, M. Kacimi, S. Michel, T. Neumann, J. X. Parreira, and G. Weikum. Efficient top-k querying over social-tagging networks. In SIGIR, 2008.
[26]
M. Shokouhi. Learning to personalize query auto-completion. In SIGIR, 2013.
[27]
M. Shokouhi and K. Radinsky. Time-sensitive query auto-completion. In SIGIR, 2012.
[28]
M. A. Soliman, I. F. Ilyas, and S. Ben-David. Supporting ranking queries on uncertain and incomplete data. VLDBJ, 19(4), 2010.
[29]
H. Vahabi, M. Ackerman, D. Loker, R. Baeza-Yates, and A. Lopez-Ortiz. Orthogonal query recommendation. In RecSys, 2013.
[30]
S. Wu, J. Tang, and B. Gao. Instant social graph search. In PAKDD12.
[31]
S. Yahia, M. Benedikt, L. Lakshmanan, and J. Stoyanovich. Efficient network aware search in collaborative tagging sites. VLDB, 2008.
[32]
J. Zobel and A. Moffat. Inverted files for text search engines. ACM Comput. Surv., 38(2), 2006.
Index Terms
- A Network-Aware Approach for Searching As-You-Type in Social Media
Recommendations
As-You-Type Social Aware Search
Modern search applications feature real-time as-you-type query search. In its elementary form, the problem consists in retrieving a set of k search results, that is, performing a search with a given prefix, and showing the top-ranked results. In this ...
User interests in social media sites: an exploration with micro-blogs
CIKM '09: Proceedings of the 18th ACM conference on Information and knowledge managementRecent technological advances in mobile-based access to social networking platforms and facilities to update information in real{time (e.g. in Facebook) have allowed an individual's online presence to be as ephemeral and dynamic in nature, as her very ...
Evidence-Based Early Rumor Verification in Social Media
Advances in Information RetrievalAbstractA plethora of studies has been conducted in the past years on rumor verification in micro-blogging platforms. However, most of them exploit the propagation network, i.e., replies and retweets to verify rumors. We argue that first, subjective ...
Comments
Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
October 2015
1998 pages
ISBN:9781450337946
DOI:10.1145/2806416
- General Chairs:
- James Bailey,
- Alistair Moffat,
- Program Chairs:
- Charu C. Aggarwal,
- Maarten de Rijke,
- Ravi Kumar,
- Vanessa Murdock,
- Timos Sellis,
- Jeffrey Xu Yu
Copyright © 2015 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]
Sponsors
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 17 October 2015
Check for updates
Author Tags
Qualifiers
- Research-article
Funding Sources
Conference
CIKM'15: 24th ACM International Conference on Information and Knowledge Management
October 18 - 23, 2015
Melbourne, Australia
Acceptance Rates
CIKM '15 Paper Acceptance Rate 165 of 646 submissions, 26%;
Overall Acceptance Rate 1,861 of 8,427 submissions, 22%
Upcoming Conference
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- View Citations1Total Citations
- 186Total Downloads
- Downloads (Last 12 months)1
- Downloads (Last 6 weeks)1
Reflects downloads up to 21 Nov 2024
Other Metrics
Citations
Cited By
View all- Lagrée PCautis BVahabi H(2017)As-You-Type Social Aware SearchACM Transactions on Intelligent Systems and Technology10.1145/30359698:5(1-31)Online publication date: 30-Jun-2017
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in