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Tomoyuki Nanno

dblp:54/3940 · DBLP profile ↗
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2ranked-venue papers
2as first author
0since 2021 · last 2006
—ORCID · none

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

Databases, data management, data science and information retrieval · 2 · 2 first-authorApplied, interdisciplinary, general and emerging computing · 2 · 2 first-author

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
Data integration and cleaning · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Data integration and cleaning › data extraction › web data extraction
RSS feed generation		 0.122006
HTML2RSS: automatic generation of RSS feed based on structure analysis of HTML document · WWW 2006
HTML2RSS: automatic generation of RSS feed based on structure analysis of HTML document · WWW 2006
Data integration and cleaning › data extraction
web data extraction		 0.122006
HTML2RSS: automatic generation of RSS feed based on structure analysis of HTML document · WWW 2006
HTML2RSS: automatic generation of RSS feed based on structure analysis of HTML document · WWW 2006

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

structure analysis · 0.1
YearPublicationVenuePosition
2006 HTML2RSS: automatic generation of RSS feed based on structure analysis of HTML document
abstract
We present a system to automatically generate RSS feeds from HTML documents that consist of time-series items with date expressions, e.g., archives of weblogs, BBSs, chats, mailing lists, site update descriptions, and event announcements. Our system extracts date expressions, performs structure analysis of a HTML document, and detects or generates titles from the document.
Tomoyuki Nanno, Manabu Okumura
 WWW1
2006 HTML2RSS: automatic generation of RSS feed based on structure analysis of HTML document
abstract
We present a system to automatically generate RSS feeds from HTML documents that consist of time-series items with date expressions, e.g., archives of weblogs, BBSs, chats, mailing lists, site update descriptions, and event announcements. Our system extracts date expressions, performs structure analysis of a HTML document, and detects or generates titles from the document.
Tomoyuki Nanno, Manabu Okumura
 WWW1