A Study of Web Print: What People Print in the Digital Era
Article No.: 23, Pages 1 - 26
Abstract
This article analyzes a proprietary log of printed web pages and aims at answering questions regarding the content people print (what), the reasons they print (why), as well as attributes of their print profile (who). We present a classification of pages printed based on their print intent and we describe our methodology for processing the print dataset used in this study. In our analysis, we study the web sites, topics, and print intent of the pages printed along the following aspects: popularity, trends, activity, user diversity, and consistency. We present several findings that reveal interesting insights into printing. We analyze our findings and discuss their impact and directions for future work.
References
[1]
Netflix recommendations (2012) Retrieved from http://techblog.netflix.com/2012/04/netflix-recommendations-beyond-5-stars.html.
[2]
M. Agosti, F. Crivellari, and G. Maria Di Nunzio. 2012. Web log analysis: A review of a decade of studies about information acquisition, inspection and interpretation of user interaction. Data Min. Knowl. Discov. 24, 3 (2012), 663--696.
[3]
A. V. Aho and M. J. Corasick. 1975. Efficient string matching: An aid to bibliographic search. Commun. ACM 18, 6 (1975), 333--340.
[4]
D. Stuart. 2014. Web Metrics for Library and Information Professionals. Facet Publishing.
[5]
R. Baeza-Yates, L. Calderan-Benavides, and C. Gonzalez-Caro. 2006. The intention behind web queries. In String Processing and Information Retrieval. Lecture Notes in Computer Science, Vol. 4209. Springer, Berlin, 98--109.
[6]
E. Baykan, M. Henzinger, L. Marian, and I. Weber. 2011. A comprehensive study of features and algorithms for URL-based topic classification. ACM Trans. Web 5, 3, Article 15.
[7]
O. Bondarenko and R. Janssen. 2005. Documents at hand: Learning from paper to improve digital technologies. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI’05). ACM, New York, 121--130.
[8]
A. Broder. 2002. A taxonomy of Web search. SIGIR Forum 36, 2, 3--10.
[9]
P. Buttfield-Addison, C. Lueg, L. Ellis, and J. Manning. 2012. “Everything goes into or out of the iPad”: The iPad, information scraps and personal information management. In Proceedings of the 24th Australian Computer-Human Interaction Conference (OzCHI’12). ACM, New York, 61--67.
[10]
R. Dooley. 2015. Paper beats digital in many ways, according to neuroscience. Retrieved from http://www.forbes.com/sites/rogerdooley/2015/09/16/paper-vs-digital/#6ae01e5f1aa2.
[11]
M. Rojas Herrera, E. Silva de Moura, M. Cristo, T. Philippe C. Silva, and A. Soares da Silva. 2010. Exploring features for the automatic identification of user goals in web search. Inf. Process. Manage. 46, 2 (2010), 131--142.
[12]
B. Jansen and A. Spink. 2006. How are we searching the web? A comparison of nine search engine query logs. Inf. Process. Manage. 42 (2006).
[13]
B. J. Jansen, D. L. Booth, and A. Spink. 2008a. Determining the informational, navigational, and transactional intent of Web queries. Inf. Process. Manage. 44, 1251--1266.
[14]
B. J. Jansen, D. L. Booth, and A. Spink. 2008b. Determining the informational, navigational, and transactional intent of web queries. Inf. Process. Manage. 44, 3, 1251--1266.
[15]
W. Jones, H. Bruce, and S. T. Dumais. 2001. Keeping found things found on the web. In Proceedings of the Conference on Information and Knowledge Management (CIKM’01).
[16]
I. Kang and G. Kim. 2003. Query type classification for web document retrieval. In Proceedings of the ACM Special Interest Group on Information Retrieval Conference (SIGIR’03). 64--71.
[17]
J. Kaye, J. Vertesi, S. Avery, A. Dafoe, S. David, L. Onaga, I. Rosero, and T. Pinch. 2006. To have and to hold: Exploring the personal archive. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI’06). ACM, New York, 275--284.
[18]
D. Kelly and J. Teevan. 2003. Implicit feedback for inferring user preference: A bibliography. In SIGIR Forum. 37, 2, 18--28.
[19]
A. Kotov, P. N. Bennett, R. W. White, S. T. Dumais, and J. Teevan. 2011. Modeling and analysis of cross-session search tasks. In Proceedings of the ACM Special Interest Group on Information Retrieval Conference (SIGIR’11).
[20]
U. Lee, Z. Liu, and J. Cho. 2005. Automatic identification of user goals in Web search. In Proceedings of the Conference on the World Wide Web (WWW’05). 391--400.
[21]
Y. Li, R. Krishnamurthy, S. Vaithyanathan, and H. V. Jagadish. 2006. Getting work done on the web: Supporting transactional queries. In Proceedings of the Special Interest Group on Information Retrieval Conference (SIGIR’06).
[22]
G. Linden, B. Smith, and J. York. 2003. Amazon.com item-to-item collaborative filtering. IEEE Int. Comput. 7, 1, 76--80.
[23]
J. Liu, P. Dolan, and E. Ronby Pedersen. 2010. Personalized news recommendation based on click behavior. In Proceedings of the Conference on Intelligent User Interfaces (IUI’10). 31--40.
[24]
R. Longadge, S. Dongre, and L. Malik. 2013. Class imbalance problem in data mining: Review. Int. J. Comput. Sci. Netw. (IJCSN’13) 2, 1.
[25]
M. Maslov, A. Golovko, I. Segalovich, and P. Braslavski. 2006. Extracting news-related queries from web query log. In Proceedings of the Conference on the World Wide Web (WWW’06). 931--932.
[26]
M. Mayer. 2009. Web history tools and revisitation support: A survey of existing approaches and directions. Found. Trends Hum.-Comput. Interact. 2, 3, 173--278.
[27]
Nancy Messieh. 2012. Repinly gives you insight into the most popular content on Pinterest. Retrived from http://tnw.to/1E4Ix.
[28]
J. C. Miller, G. Rae, and F. Schaefer. 2001. Modifications of kleinberg’s hits algorithm using matrix exponentiation and weblog records. In Proceedings of the ACM Special Interest Group on Information Retrieval Conference (SIGIR’01). 444--445.
[29]
D. Mladenic. 1998. Turning Yahoo into an Automatic Web-Page Classifier. In Proceedings of the 13th European Conference on Artificial Intelligence (ECAI’98). 473--474.
[30]
H. Obendorf, H. Weinreich, E. Herder, and M. Mayer. 2007. Web page revisitation revisited: Implications of a long-term click-stream study of browser usage. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI’07). ACM, New York, 597--606.
[31]
X. Qi and B. D. Davison. 2009. Web page classification: Features and algorithms. ACM Comput. Surv. 41, 2, Article 12.
[32]
D. E. Rose and D. Levinson. 2004. In understanding user goals in web search. In Proceedings of the Conference on the World Wide Web (WWW’04). 13--19.
[33]
Abigail J. Sellen and Richard H. R. Harper. 2003. The Myth of the Paperless Office. MIT Press, Cambridge.
[34]
X. Shi and C. C. Yang. 2007. Mining related queries from web search engine query logs using an improved association rule mining model. J. Am. Soc. Info. Sci. Technol. 58, 12 (2007), 1871--1883.
[35]
R. Srikant and Y. Yang. 2001. Mining web logs to improve website organization. In Proceedings of the Conference on the World Wide Web (WWW’01). 430--437.
[36]
L. Tauscher and S. Greenberg. 1997. How people revisit web pages: Empirical findings and implications for the design of history systems. Int. J. Hum.-Comput. Studies 47, 1 (1997), 97--137.
[37]
J. Teevan, E. Adar, R. Jones, and M. Potts. 2006. Information re-retrieval: Repeat queries in Yahoo’s logs. In Proceedings of the ACM Special Interest Group on Information Retrieval Conference (SIGIR’06). 151--158.
[38]
J. Tolle. 1983. Transactional log analysis: Online catalogs. In Proceedings of the ACM Special Interest Group on Information Retrieval Conference (SIGIR’83). 147--160.
[39]
S. K. Tyler and J. Teevan. 2010. Large scale query log analysis of re-finding. In Proceedings of the Conference on Web Search and data Mining (WSDM’10). 191--200.
[40]
S. Wedig and O. Madani. 2006. A large-scale analysis of query logs for assessing personalization opportunities. In Proceedings of the Conference on Knowledge Discovery and Dat Mining (KDD’06).
[41]
R. W. White, P. N. Bennett, and Susan T. Dumais. 2010. Predicting short-term interests using activity-based search context. In Proceedings of the Conference on Information and Knowledge Management (CIKM’10). 1009--1018.
[42]
S. Whittaker and J. Hirschberg. 2001. The character, value, and management of personal paper archives. ACM Trans. Comput. Hum. Interact. 8 (2001), 150--170.
[43]
Z. Zhang and O. Nasraoui. 2008. Mining search engine query logs for social filtering-based query recommendation. Appl. Soft. Comput. 8, 4 (2008), 1326--1334.
Index Terms
- A Study of Web Print: What People Print in the Digital Era
Recommendations
Heterogeneous material micro-transfer by ink-jet print assisted mould filling
Graphical abstractDisplay Omitted Highlights A novel technological approach combining IJP and micro-transfer moulding is studied. Heterogeneous material pattern transfer is achieved in a two step process. The proposed process is optimized and ...
Projection lithography to print thick resist patterns with triangular and semi-circular cross-section profiles
Patterning technology to print thick resist patterns with triangular and semi-circular cross-section profiles was investigated for applying to fabrication of light-guide plates and lens arrays, surface texturization of solar cells, and others. Positive ...
Inkjet 4D Print: Self-folding Tessellated Origami Objects by Inkjet UV Printing
We propose Inkjet 4D Print, a self-folding fabrication method of 3D origami tessellations by printing 2D patterns on both sides of a heat-shrinkable base sheet, using a commercialized inkjet ultraviolet (UV) printer. Compared to the previous folding-...
Comments
Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
November 2017
257 pages
ISSN:1559-1131
EISSN:1559-114X
DOI:10.1145/3127338
- Editors:
- Brian D. Davison,
- Marianne Winslett
Copyright © 2017 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]
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 25 July 2017
Accepted: 01 March 2017
Revised: 01 March 2017
Received: 01 May 2016
Published in TWEB Volume 11, Issue 4
Check for updates
Author Tags
Qualifiers
- Research-article
- Research
- Refereed
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 225Total Downloads
- Downloads (Last 12 months)8
- Downloads (Last 6 weeks)2
Reflects downloads up to 03 Jan 2025
Other Metrics
Citations
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