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Omer Kareem

dblp:99/895 · DBLP profile ↗
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3ranked-venue papers
0as first author
0since 2021 · last 2008
0000-0002-6258-342XORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 3

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Databases, data mining, and information retrieval
2 papers
Information retrieval · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Information retrieval › text summarization › structured summarization
hierarchical summarization
0.122006
News to go: hierarchical text summarization for mobile devices · SIGIR 2006
Hierarchical text summarization for WAP-enabled mobile devices · SIGIR 2005
Information retrieval
text summarization
0.122006
News to go: hierarchical text summarization for mobile devices · SIGIR 2006
Hierarchical text summarization for WAP-enabled mobile devices · SIGIR 2005
Information retrieval › web search
mobile search
0.012006
News to go: hierarchical text summarization for mobile devices · SIGIR 2006
Information retrieval › text summarization
news summarization
0.012006
News to go: hierarchical text summarization for mobile devices · SIGIR 2006

Methods — techniques the papers use, named apart from their topics

user evaluation · 0.1
YearPublicationVenuePosition
2008 Hierarchical summarization for delivering information to mobile devices
Jahna Otterbacher, Dragomir R. Radev, Omer Kareem
Inf. Process. Manag.3
2006 News to go: hierarchical text summarization for mobile devices
abstract
We present an evaluation of a novel hierarchical text summarization method that allows users to view summaries of Web documents from small, mobile devices. Unlike previous approaches, ours does not require the documents to be in HTML since it infers a hierarchical structure automatically. Currently, the method is used to summarize news articles sent to a Web mail account in plain text format. Subjects used a Web-enabled mobile phone emulator to access the account's inbox and view the summarized news articles. They then used the summaries to complete several information-seeking tasks, which involved answering factual questions about the stories. In comparing the hierarchical text summary setting to that in which subjects were given the full text articles, there was no significant difference in task accuracy or the time taken to complete the task. However, in the hierarchical summarization setting, the number of bytes transferred per user request is less than half that of the full text case. Finally, in comparing the new method to three other summarization methods, subjects achieved significantly better accuracy on the tasks when using hierarchical summaries.
Jahna Otterbacher, Dragomir R. Radev, Omer Kareem
SIGIR3
2005 Hierarchical text summarization for WAP-enabled mobile devices
abstract
We present WAP MEAD, a WAP-enabled text summarization system. It incorporates a state-of-the art text summarizer enhanced to produce hierarchical summaries that are appropriate for various types of mobile devices, including cellular phones.
Dragomir R. Radev, Omer Kareem, Jahna Otterbacher
SIGIR2