What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Information retrieval
- World Wide Web
Information retrieval, Artificial intelligence, World Wide Web, Language model and Set are his primary areas of study.
His Information retrieval research is multidisciplinary, incorporating perspectives in Representation, Entity linking and Information needs.
His research integrates issues of Machine learning and Natural language processing in his study of Artificial intelligence.
His work on The Internet as part of general World Wide Web research is frequently linked to Industrial research, Commonwealth and Enterprise data management, bridging the gap between disciplines.
His biological study deals with issues like Legal expert system, which deal with fields such as Probabilistic logic.
His study explores the link between Semantic search and topics such as Data set that cross with problems in Knowledge base.
His most cited work include:
- Formal models for expert finding in enterprise corpora (507 citations)
- A language modeling framework for expert finding (190 citations)
- Expertise Retrieval (151 citations)
What are the main themes of his work throughout his whole career to date?
Krisztian Balog mostly deals with Information retrieval, World Wide Web, Knowledge base, Ranking and Artificial intelligence.
His study on Semantic search is often connected to Focus as part of broader study in Information retrieval.
His work carried out in the field of World Wide Web brings together such families of science as Language model, Field and Service.
His Knowledge base research incorporates themes from Interpretation, Natural language and Table.
His research in Ranking intersects with topics in Query language, Web search query, Web query classification and Relevance.
The study incorporates disciplines such as Machine learning and Natural language processing in addition to Artificial intelligence.
He most often published in these fields:
- Information retrieval (69.37%)
- World Wide Web (20.27%)
- Knowledge base (15.32%)
What were the highlights of his more recent work (between 2017-2021)?
- Information retrieval (69.37%)
- Knowledge base (15.32%)
- Table (7.21%)
In recent papers he was focusing on the following fields of study:
Krisztian Balog spends much of his time researching Information retrieval, Knowledge base, Table, Information access and Information needs.
Krisztian Balog interconnects Ranking, Crowdsourcing and Natural language in the investigation of issues within Information retrieval.
His study on Table also encompasses disciplines like
- Similarity which is related to area like Supervised learning,
- Row which intersects with area such as Ranking, Data mining and Schema.
Information needs is a primary field of his research addressed under World Wide Web.
His World Wide Web study frequently involves adjacent topics like Variety.
His work in Question answering addresses issues such as Test data, which are connected to fields such as Artificial intelligence.
Between 2017 and 2021, his most popular works were:
- Ad Hoc Table Retrieval using Semantic Similarity (56 citations)
- Coached Conversational Preference Elicitation: A Case Study in Understanding Movie Preferences (38 citations)
- Table2Vec: Neural Word and Entity Embeddings for Table Population and Retrieval (34 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Information retrieval
- Machine learning
Krisztian Balog mainly investigates Information retrieval, Table, Knowledge base, Artificial intelligence and Information access.
Krisztian Balog is involved in the study of Information retrieval that focuses on Semantic search in particular.
His study focuses on the intersection of Table and fields such as Similarity with connections in the field of Supervised learning.
His study in the field of Entity linking is also linked to topics like Process.
The concepts of his Artificial intelligence study are interwoven with issues in Machine learning and Natural language processing.
Krisztian Balog has included themes like Ranking, Data mining and Baseline in his Row study.
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