Sökning: "memory-based learning"

Visar resultat 1 - 5 av 7 avhandlingar innehållade orden memory-based learning.

1. 1. Data-driven syntactic analysis

   Författare :Beata Megyesi; KTH; []
   Nyckelord :natural language processing; machine learning; data-driven methods; part-of-speech tagging; chunking; shallow parsing; evaluation; hidden Markov modeling; maximum entropy learning; memory-based learning; transformation-based learning; morphology; syn;

   Sammanfattning : .... LÄS MER

3. 2. Inductive Dependency Parsing of Natural Language Text

   Författare :Joakim Nivre; Walter Daelemans; Växjö universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; natural language parsing; dependency parsing; memory-based learning; treebank parsing; Systems engineering; Systemteknik; Computer and Information Sciences Computer Science; Data- och informationsvetenskap;

   Sammanfattning : This thesis investigates new methods for syntactic parsing of unrestricted natural language text under requirements of robustness and disambiguation. A parsing system is required to assign to every sentence in a text at least one analysis (robustness) and at most one analysis (disambiguation). LÄS MER

4. 3. MaltParser -- An Architecture for Inductive Labeled Dependency Parsing

   Författare :Johan Hall; Joakim Nivre; Welf Löwe; Martin Volk; Växjö universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Dependency Parsing; Support Vector Machines; Machine Learning; Language technology; Språkteknologi; Computer and Information Sciences Computer Science; Data- och informationsvetenskap;

   Sammanfattning : This licentiate thesis presents a software architecture for inductive labeled dependency parsing of unrestricted natural language text, which achieves a strict modularization of parsing algorithm, feature model and learning method such that these parameters can be varied independently. The architecture is based on the theoretical framework of inductive dependency parsing by Nivre \citeyear{nivre06c} and has been realized in MaltParser, a system that supports several parsing algorithms and learning methods, for which complex feature models can be defined in a special description language. LÄS MER

5. 4. Transition-Based Natural Language Parsing with Dependency and Constituency Representations

   Författare :Johan Hall; Joakim Nivre; Welf Löwe; Sandra Kübler; Växjö universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Natural Language Parsing; Syntactic Parsing; Dependency Structure; Phrase Structure; Machine Learning; Computer science; Datavetenskap; Computer and Information Sciences Computer Science; Data- och informationsvetenskap;

   Sammanfattning : Denna doktorsavhandling undersöker olika aspekter av automatisk syntaktisk analys av texter på naturligt språk. En parser eller syntaktisk analysator, som vi definierar den i denna avhandling, har till uppgift att skapa en syntaktisk analys för varje mening i en text på naturligt språk. LÄS MER

7. 5. Algorithms and Representations for Personalised Information Access

   Författare :Rickard Cöster; Lars Asker; Haym Hirsh; Stockholms universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; Computer science; Datavetenskap;

   Sammanfattning : Personalised information access systems use historical feedback data, such as implicit and explicit ratings for textual documents and other items, to better locate the right or relevant information for individual users.Three topics in personalised information access are addressed: learning from relevance feedback and document categorisation by the use of concept-based text representations, the need for scalable and accurate algorithms for collaborative filtering, and the integration of textual and collaborative information access. LÄS MER