Name
Abstract | ||
|---|---|---|
In this paper we address the difficulty of clipping articles from mobile apps. We propose a service called UniClip that allows a user to save the full content of an article by snapping a screenshot part of it. UniClip leverages a huge amount of indexed web data to mine the article by starting with a snapped screenshot. We propose approaches to solve three challenges: (1) how to represent a screenshot; (2) how to formulate effective queries for retrieving a full article; and (3) how to rank the best URL at the top from multiple search result lists. Experimental results indicate that our approach is effective in achieving as high an (F_1) measure as 0.905, which outperforms the best of three baseline methods by 18 points. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1007/s41019-016-0012-2 | Data Science and Engineering |
Keywords | Field | DocType |
Universal clipping, Search, Screenshots, Article clipping, Mobile apps | Data mining,World Wide Web,Information retrieval,Computer science,Mobile apps,Clipping (audio) | Journal |
Volume | Issue | ISSN |
1 | 2 | 2364-1541 |
Citations | PageRank | References |
2 | 0.36 | 27 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ruihua Song | 1 | 1138 | 59.33 |
| Kazutoshi Umemoto | 2 | 19 | 3.12 |
| Jian-yun Nie | 3 | 3681 | 238.61 |
| Xing Xie | 4 | 9105 | 527.49 |
| Katsumi Tanaka | 5 | 1349 | 160.89 |
| Yong Rui | 6 | 7052 | 449.08 |