What is she best known for?
The fields of study she is best known for:
- Artificial intelligence
- Information retrieval
- World Wide Web
Vanessa Murdock mostly deals with Information retrieval, Search engine, Artificial intelligence, Web search query and World Wide Web.
The various areas that Vanessa Murdock examines in her Information retrieval study include Language model and Search advertising.
Her biological study deals with issues like Natural language processing, which deal with fields such as Speech recognition and Translation.
The concepts of her Web search query study are interwoven with issues in Layer, Query expansion and Database.
Vanessa Murdock has included themes like Data mining and Leverage in her World Wide Web study.
Her Data mining research includes elements of Graph, Classifier, Content farm, Cluster analysis and Spamdexing.
Her most cited work include:
- Know your neighbors: web spam detection using the web topology (306 citations)
- Placing flickr photos on a map (262 citations)
- "I'm eating a sandwich in Glasgow": modeling locations with tweets (211 citations)
What are the main themes of her work throughout her whole career to date?
Her primary scientific interests are in Information retrieval, World Wide Web, Data mining, Ranking and Web search query.
In her work, Word is strongly intertwined with Set, which is a subfield of Information retrieval.
Her work on Social media, Information access, Linked data and Information needs as part of her general World Wide Web study is frequently connected to Mobile search, thereby bridging the divide between different branches of science.
Her studies in Data mining integrate themes in fields like Classifier and Cluster analysis.
Her Ranking study combines topics in areas such as Web page, Feature, Rank and Natural language processing.
Her Search engine study combines topics from a wide range of disciplines, such as Ranking and Database.
She most often published in these fields:
- Information retrieval (59.00%)
- World Wide Web (33.00%)
- Data mining (19.00%)
What were the highlights of her more recent work (between 2012-2019)?
- World Wide Web (33.00%)
- Information access (7.00%)
- Session (3.00%)
In recent papers she was focusing on the following fields of study:
Her primary areas of study are World Wide Web, Information access, Session, Knowledge management and Data science.
Her research is interdisciplinary, bridging the disciplines of Information retrieval and World Wide Web.
Her Geographic information retrieval, Search engine indexing and Information extraction study in the realm of Information retrieval connects with subjects such as Geographic information system and Field.
She combines subjects such as Programming language, Semantics and Multimedia with her study of Session.
Her Knowledge management study integrates concerns from other disciplines, such as Session, Local search and Service.
Her work carried out in the field of Data science brings together such families of science as State, Tracing and Geolocation.
Between 2012 and 2019, her most popular works were:
- Modeling locations with social media (51 citations)
- Geographic information retrieval: progress and challenges in spatial search of text (33 citations)
- The Benchmark as a Research Catalyst: Charting the Progress of Geo-prediction for Social Multimedia (8 citations)
In her most recent research, the most cited papers focused on:
- Artificial intelligence
- World Wide Web
- Information retrieval
Social media, World Wide Web, Information retrieval, Index and Search engine are her primary areas of study.
Her Social media research is multidisciplinary, relying on both Language model, Ground truth and Geotagging.
The World Wide Web study combines topics in areas such as Artificial intelligence and Computer vision.
Her research links Point of interest with Information retrieval.
She has researched Index in several fields, including Ranking, Salient, Web search query and Rank.
Her biological study spans a wide range of topics, including Ranking and Information needs.
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