NLPIR\/ICTCLA2018 ACADEMIC SEMINAR 2st ISSUE<\/span><\/span><\/b><\/p>\n

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\u00a0 \u00a0 \u00a0 \u00a0 INTRO<\/span><\/span><\/b>\u81ea\u7136\u8bed\u8a00\u5904\u7406\u4e0e\u4fe1\u606f\u68c0\u7d22\u5171\u4eab\u5e73\u53f09h\u0006c0Y4Y\u001bt\/z\u001fA\u0012P<\/span><\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0 <\/strong>In the new semester, our Lab, Web Search Mining and Security Lab, plans to hold an academic seminar every Wednesdays, and each time a keynote speaker will share understanding of papers published in recent years with you.<\/span><\/span><\/span>\u81ea\u7136\u8bed\u8a00\u5904\u7406\u4e0e\u4fe1\u606f\u68c0\u7d22\u5171\u4eab\u5e73\u53f0’I&b-c j\u001b?4M+_\u0013w0o;p<\/span><\/p>\n

\u00a0<\/span><\/span>\u81ea\u7136\u8bed\u8a00\u5904\u7406\u4e0e\u4fe1\u606f\u68c0\u7d22\u5171\u4eab\u5e73\u53f0\u001aW\u0016N\u0012H\u000ee1A<\/span><\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0 <\/strong>Arrangement<\/span><\/span><\/b>\u81ea\u7136\u8bed\u8a00\u5904\u7406\u4e0e\u4fe1\u606f\u68c0\u7d22\u5171\u4eab\u5e73\u53f0\u0001v O
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\u00a0 \u00a0 \u00a0 \u00a0 <\/strong>This week’s seminar is organized as follows:<\/span><\/span><\/span><\/p>\n

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\u00a0 \u00a0 \u00a0 \u00a0 <\/strong>1. The seminar time is 1.pm, Wed<\/b>, at Zhongguancun Technology Park ,Building 5, 1036.<\/span><\/span><\/span>\u81ea\u7136\u8bed\u8a00\u5904\u7406\u4e0e\u4fe1\u606f\u68c0\u7d22\u5171\u4eab\u5e73\u53f00]\u0019n%b-Z”l&\\!M\u0003s”x\u0017W,_\u0014E\u0012iZ<\/span><\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0 <\/strong>2. The lecturer is Nihad<\/b>, the paper’s title is Growing Wikipedia Across Languages via Recommendation<\/b>.<\/span><\/span><\/span><\/p>\n

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\u00a0 \u00a0 \u00a0 \u00a0 <\/strong>3. The seminar will be hosted Gang Wang.<\/span><\/span><\/span><\/p>\n

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\u00a0 \u00a0 \u00a0 \u00a0 <\/strong>4. Attachment is the paper of this seminar, please download in advance<\/span><\/span><\/span>\u81ea\u7136\u8bed\u8a00\u5904\u7406\u4e0e\u4fe1\u606f\u68c0\u7d22\u5171\u4eab\u5e73\u53f0\u001ei’S\u0019`\u000fv\u0013r\u000eO\u0007y
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\u00a0<\/span><\/span>\u81ea\u7136\u8bed\u8a00\u5904\u7406\u4e0e\u4fe1\u606f\u68c0\u7d22\u5171\u4eab\u5e73\u53f0\u001bK.^\u0017q0f#U(T\u000fs0s3v\\)w,Y<\/span><\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0 <\/strong>Everyone interested in this topic is welcomed to join us. the following is the abstract for this week\u2019s paper <\/span><\/span><\/p>\n

J1y’w5]\u000bC\u0015o\bC0<\/span><\/p>\n

\u00a0\u81ea\u7136\u8bed\u8a00\u5904\u7406\u4e0e\u4fe1\u606f\u68c0\u7d22\u5171\u4eab\u5e73\u53f0\u0011X3E\u0018u\u0010I)X\u0007~9z<\/span><\/p>\n

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Growing Wikipedia Across Languages via Recommendation<\/span><\/span><\/p>\n
\u0002p”}\u001aX\u0013f,k\u0012W-F.b+N”l\u0011X0<\/span><\/p>\n
Ellery Wulczyn\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 <\/span>Robert West\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 <\/span>Leila Zia\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 <\/span>Jure Leskovec<\/span><\/span>\u81ea\u7136\u8bed\u8a00\u5904\u7406\u4e0e\u4fe1\u606f\u68c0\u7d22\u5171\u4eab\u5e73\u53f0&B8F\u0005`\/p’AW\u001cQ<\/span><\/p>\n
Abstract<\/span><\/span>\u81ea\u7136\u8bed\u8a00\u5904\u7406\u4e0e\u4fe1\u606f\u68c0\u7d22\u5171\u4eab\u5e73\u53f0-c\u0018l;l*Z*@\u0015W9M<\/span><\/p>\n
\u00a0 \u00a0 \u00a0 \u00a0 <\/strong>The differentWikipedia language editions vary dramatically in how comprehensive they are. As a result, most language editions contain only a small fraction of the sum of information that exists across all Wikipedias. In this paper, we present an approach to filling gaps in article coverage across different Wikipedia editions. Our main contribution is an end-to-end system for recommending articles for creation that exist in one language but are missing in another. The system involves identifying missing articles, ranking the missing articles according to their importance, and recommending important missing articles to editors based on their interests. We empirically validate our models in a controlled experiment involving 12,000 French Wikipedia editors. We find that personalizing recommendations increases editor engagement by a factor of two. Moreover, recommending articles increases their chance of being created by a factor of 3.2. Finally, articles created as a result of our recommendations are of comparable quality to organically created articles. Overall, our system leads to more engaged editors and faster growth of Wikipedia with no effect on its quality.<\/span><\/span>\u81ea\u7136\u8bed\u8a00\u5904\u7406\u4e0e\u4fe1\u606f\u68c0\u7d22\u5171\u4eab\u5e73\u53f0\u0003b9w!J5^!T,D\fP\u001cp<\/span><\/p>\n<\/div>\n
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