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Sidharth Goyal

dblp:166/8354 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2015
—ORCID · none

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

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

Databases, data mining, and information retrieval
1 paper
Graph data management · 33% Information retrieval · 33% Recommender systems · 33%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Recommender systems › graph-based recommendation
edge recommendation
0.212015
VIIQ: Auto-Suggestion Enabled Visual Interface for Interactive Graph Query Formulation · Proc. VLDB Endow. 2015
Graph data management › graph query
graph query formulation
0.212015
VIIQ: Auto-Suggestion Enabled Visual Interface for Interactive Graph Query Formulation · Proc. VLDB Endow. 2015
Information retrieval › search interfaces
visual query interface
0.212015
VIIQ: Auto-Suggestion Enabled Visual Interface for Interactive Graph Query Formulation · Proc. VLDB Endow. 2015

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

edge suggestion algorithm · 0.2
YearPublicationVenuePosition
2015 VIIQ: Auto-Suggestion Enabled Visual Interface for Interactive Graph Query Formulation
abstract
We present VIIQ (pronounced as wick), an interactive and iterative visual query formulation interface that helps users construct query graphs specifying their exact query intent. Heterogeneous graphs are increasingly used to represent complex relationships in schemaless data, which are usually queried using query graphs. Existing graph query systems offer little help to users in easily choosing the exact labels of the edges and vertices in the query graph. VIIQ helps users easily specify their exact query intent by providing a visual interface that lets them graphically add various query graph components, backed by an edge suggestion mechanism that suggests edges relevant to the user's query intent. In this demo we present: 1) a detailed description of the various features and user-friendly graphical interface of VIIQ , 2) a brief description of the edge suggestion algorithm, and 3) a demonstration scenario that we intend to show the audience.
Nandish Jayaram, Sidharth Goyal, Chengkai Li 0001
Proc. VLDB Endow.2