Demo Data from SIGIR 2026 / reviewers in the wild / expert
Dave Herman
dblp:158/7996
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2013
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 1
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.
| Software engineering, system software, and programming languages
1 paper |
Compilers and program optimization · 100% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Parallel and multicore computing · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Compilers and program optimization › parsing
parallel parsing |
0.2 | 1 | 2013 | HPar: A practical parallel parser for HTML-taming HTML complexities for parallel parsing · ACM Trans. Archit. Code Optim. 2013 |
Compilers and program optimization › parallelization
speculative parallelization |
0.2 | 1 | 2013 | HPar: A practical parallel parser for HTML-taming HTML complexities for parallel parsing · ACM Trans. Archit. Code Optim. 2013 |
Parallel and multicore computing
data parallelism |
0.0 | 1 | 2013 | HPar: A practical parallel parser for HTML-taming HTML complexities for parallel parsing · ACM Trans. Archit. Code Optim. 2013 |
Methods — techniques the papers use, named apart from their topics
speculative parallelization · 0.3pipelining · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2013 | HPar: A practical parallel parser for HTML-taming HTML complexities for parallel parsingabstractParallelizing HTML parsing is challenging due to the complexities of HTML documents and the inherent dependencies in its parsing algorithm. As a result, despite numerous studies in parallel parsing, HTML parsing remains sequential today. It forms one of the final barriers for fully parallelizing browser operations to minimize the browser’s response time—an important variable for user experiences, especially on portable devices. This article provides a comprehensive analysis on the special complexities of parallel HTML parsing and presents a systematic exploration in overcoming those difficulties through specially designed speculative parallelizations. This work develops, to the best of our knowledge, the first pipelining and data-level parallel HTML parsers. The data-level parallel parser, named HPar , achieves up to 2.4× speedup on quadcore devices. This work demonstrates the feasibility of efficient, parallel HTML parsing for the first time and offers a set of novel insights for parallel HTML parsing Zhijia Zhao 0001, Michael Bebenita, Dave Herman, Xipeng Shen |
ACM Trans. Archit. Code Optim. | 3 |