Information Retrieval(IR) systems are gaining importance due to wide range of applications like recommender systems, search engines, etc., however, most of the IR systems use statistical methods built on top of bag-of-words approach for text retrieval. Graph-of-words approach is an alternative to bag-of-words approach that uses graph theoretic methods to rank keywords and related documents. We represent text documents as graphs whose vertices correspond to the unique terms belonging to the document. The edges represent co-occurrences between the terms. The underlying assumption is that the terms that co-occur have some sort of semantic relationship that can be harnessed for IR systems. The significant terms can be extracted using graph centrality measures. In this book, we have proposed a novel graph-of-words indexing technique using eigenvector scores that uses case separation for Gujarati language. We compared the performance of IR systems of our approach over the classical bag-of-words approach, mean average precision (MAP) values obtained in our experiments show that our approach has shown significant improvement over classical approaches.
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
Dr. Hardik Joshi is an Assistant Professor with the Dept. of Computer Sc., Gujarat University, India. His research interests include Natural Language Processing and Information Retrieval.
„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.
Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Information Retrieval(IR) systems are gaining importance due to wide range of applications like recommender systems, search engines, etc., however, most of the IR systems use statistical methods built on top of bag-of-words approach for text retrieval. Graph-of-words approach is an alternative to bag-of-words approach that uses graph theoretic methods to rank keywords and related documents. We represent text documents as graphs whose vertices correspond to the unique terms belonging to the document. The edges represent co-occurrences between the terms. The underlying assumption is that the terms that co-occur have some sort of semantic relationship that can be harnessed for IR systems. The significant terms can be extracted using graph centrality measures. In this book, we have proposed a novel graph-of-words indexing technique using eigenvector scores that uses case separation for Gujarati language. We compared the performance of IR systems of our approach over the classical bag-of-words approach, mean average precision (MAP) values obtained in our experiments show that our approach has shown significant improvement over classical approaches. 164 pp. Englisch. Bestandsnummer des Verkäufers 9786200082763
Anzahl: 2 verfügbar
Anbieter: moluna, Greven, Deutschland
Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Joshi Dr. HardikDr. Hardik Joshi is an Assistant Professor with the Dept. of Computer Sc., Gujarat University, India. His research interests include Natural Language Processing and Information Retrieval.Information Retrieval(IR) . Bestandsnummer des Verkäufers 298918778
Anzahl: Mehr als 20 verfügbar
Anbieter: preigu, Osnabrück, Deutschland
Taschenbuch. Zustand: Neu. Identification of Significant Keywords from Gujarati Text Documents | Hardik Joshi | Taschenbuch | 164 S. | Englisch | 2019 | LAP LAMBERT Academic Publishing | EAN 9786200082763 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Bestandsnummer des Verkäufers 116849106
Anzahl: 5 verfügbar
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Information Retrieval(IR) systems are gaining importance due to wide range of applications like recommender systems, search engines, etc., however, most of the IR systems use statistical methods built on top of bag-of-words approach for text retrieval. Graph-of-words approach is an alternative to bag-of-words approach that uses graph theoretic methods to rank keywords and related documents. We represent text documents as graphs whose vertices correspond to the unique terms belonging to the document. The edges represent co-occurrences between the terms. The underlying assumption is that the terms that co-occur have some sort of semantic relationship that can be harnessed for IR systems. The significant terms can be extracted using graph centrality measures. In this book, we have proposed a novel graph-of-words indexing technique using eigenvector scores that uses case separation for Gujarati language. We compared the performance of IR systems of our approach over the classical bag-of-words approach, mean average precision (MAP) values obtained in our experiments show that our approach has shown significant improvement over classical approaches.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 164 pp. Englisch. Bestandsnummer des Verkäufers 9786200082763
Anzahl: 1 verfügbar
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Information Retrieval(IR) systems are gaining importance due to wide range of applications like recommender systems, search engines, etc., however, most of the IR systems use statistical methods built on top of bag-of-words approach for text retrieval. Graph-of-words approach is an alternative to bag-of-words approach that uses graph theoretic methods to rank keywords and related documents. We represent text documents as graphs whose vertices correspond to the unique terms belonging to the document. The edges represent co-occurrences between the terms. The underlying assumption is that the terms that co-occur have some sort of semantic relationship that can be harnessed for IR systems. The significant terms can be extracted using graph centrality measures. In this book, we have proposed a novel graph-of-words indexing technique using eigenvector scores that uses case separation for Gujarati language. We compared the performance of IR systems of our approach over the classical bag-of-words approach, mean average precision (MAP) values obtained in our experiments show that our approach has shown significant improvement over classical approaches. Bestandsnummer des Verkäufers 9786200082763
Anzahl: 1 verfügbar