Demo Data from EDBT 2026 / reviewers in the wild / expert
Shaishav Kumar
dblp:10/8313
· DBLP profile ↗
5ranked-venue papers
2as first author
0since 2021 · last 2014
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 3 · 1 first-authorDatabases, data management, data science and information retrieval · 2 · 1 first-authorGraphics, computer vision, multimedia, augmented reality and games · 1 · 1 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
4 papers |
Information retrieval · 100% | |
| Artificial intelligence
1 paper |
Information extraction and text analysis · 100% |
Topics — the 8 heaviest of 10, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Information retrieval
hashing |
0.1 | 1 | 2011 | Learning Hash Functions for Cross-View Similarity Search · IJCAI 2011 |
Information retrieval › hashing › binary code learning
learned hash functions |
0.1 | 1 | 2011 | Learning Hash Functions for Cross-View Similarity Search · IJCAI 2011 |
Information retrieval
similarity search |
0.1 | 1 | 2011 | Learning Hash Functions for Cross-View Similarity Search · IJCAI 2011 |
Information retrieval › search engines › semantic search › entity retrieval
people search |
0.1 | 1 | 2010 | Multilingual people search · SIGIR 2010 |
Information retrieval
query suggestion |
0.1 | 1 | 2010 | Suggesting related topics in web search · SIGIR 2010 |
Information retrieval › query understanding
spelling correction |
0.1 | 1 | 2010 | Hashing-Based Approaches to Spelling Correction of Personal Names · EMNLP 2010 |
Information retrieval
web search |
0.1 | 1 | 2010 | Suggesting related topics in web search · SIGIR 2010 |
Information retrieval › search engines
search result analysis |
0.0 | 1 | 2010 | Suggesting related topics in web search · SIGIR 2010 |
Methods — techniques the papers use, named apart from their topics
hashing · 0.2multilingual search · 0.1demonstration system · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2014 | Online Gaming for Crowd-sourcing Phrase-equivalents
A. Kumaran 0001, Melissa Densmore, Shaishav Kumar |
COLING | 3 |
| 2011 | Learning Hash Functions for Cross-View Similarity Search
Shaishav Kumar, Raghavendra Udupa |
IJCAI | 1 |
| 2010 | Hashing-Based Approaches to Spelling Correction of Personal Names
Raghavendra Udupa, Shaishav Kumar |
EMNLP | 2 |
| 2010 | Multilingual people searchabstractPeople Search is an important search service with multiple applications (eg. looking up a friend on Facebook, finding colleagues in corporate email directories etc). With the proportion of non-English users on a steady rise, people search services are being used by users from diverse language demographics. Users may issue name search queries against these directories in languages other than the language of the directory, in which case the present monolingual name search approaches will not work. In this demo, we present a Multilingual People Search system capable of performing fast name lookups on large user directories, independent of the directory language. Our system has applications in areas like social networking, enterprise search and email address book search. Shaishav Kumar, Raghavendra Udupa |
SIGIR | 1 |
| 2010 | Suggesting related topics in web searchabstractSuggesting topics that are related to user's goal or interest is very important in web search. However, search engines today focus on suggesting mainly reformulations and lexical variants of the query mined from query logs. In this demonstration, we show a system that can suggest related topics for a query based on the top search results for the query. It can help users in exploring the topics related to their information need. The topic suggestion system can be integrated with any search engine or it can be easily installed on the client machine as a browser plugin. Santosh Raju, Shaishav Kumar, Raghavendra Udupa |
SIGIR | 2 |