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Hamid Haidarian Shahri

dblp:15/5874 · DBLP profile ↗
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4ranked-venue papers
4as first author
0since 2021 · last 2010
—ORCID · none

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

Artificial intelligence and machine learning · 3 · 3 first-authorGraphics, computer vision, multimedia, augmented reality and games · 2 · 2 first-authorDatabases, data management, data science and information retrieval · 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
1 paper
Information retrieval · 56% Graph data management · 44%
Artificial intelligence
1 paper
Knowledge representation and reasoning · 77% Question answering and dialogue systems · 23%

Topics — the 4 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Graph data management › graph data model
RDF data model
0.112010
Semantic Search in Linked Data: Opportunities and Challenges · AAAI 2010
Information retrieval › search engines
semantic search
0.112010
Semantic Search in Linked Data: Opportunities and Challenges · AAAI 2010
Knowledge, reasoning and agents › Knowledge representation and reasoning › ontology
ontology matching
0.112008
Finding Ontological Correspondences for a Domain-Independent Natural Language Dialog Agent · AAAI 2008
Information retrieval
keyword search
0.012010
Semantic Search in Linked Data: Opportunities and Challenges · AAAI 2010
YearPublicationVenuePosition
2010 Semantic Search in Linked Data: Opportunities and Challenges
abstract
In this abstract, we compare semantic search (in the RDF model) with keyword search (in the relational model), and illustrate how these two search paradigms are different. This comparison addresses the following questions: (1) What can semantic search achieve that keyword search can not (in terms of behavior)? (2) Why is it difficult to simulate semantic search, using keyword search on the relational data model? We use the term keyword search, when the search is performed on data stored in the relational data model, as in traditional relational databases, and an example of keyword search in databases is [Hri02]. We use the term semantic search, when the search is performed on data stored in the RDF data model. Note that when the data is modeled in RDF, it inherently contains explicit typed relations or semantics, and hence the use of the term “semantic search.” Let us begin with an example, to illustrate the differences between semantic search and keyword search.
Hamid Haidarian Shahri
AAAI1
2008 Finding Ontological Correspondences for a Domain-Independent Natural Language Dialog Agent
Hamid Haidarian Shahri, Donald Perlis
AAAI1
2004 Social Control Mechanisms to Coordinate an Unreliable Agent Society
Hamid Haidarian Shahri, Mohammad Reza Meybodi
COORDINATION1
2004 A Flexible Fuzzy Expert System for Fuzzy Duplicate Elimination in Data Cleaning
Hamid Haidarian Shahri, Ahmad Abdollahzadeh Barforoush
DEXA1