10 Result(s)
within
Ganesh Ramakrishnan
Mathematical Logic and Formal Languages
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Chapter and Conference Paper
Difficulty-Controllable Multi-hop Question Generation from Knowledge Graphs
Knowledge graphs have become ubiquitous data sources and their utility has been amplified by the research on ability to answer carefully crafted questions over knowledge graphs. We investigate the problem of q...
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Chapter and Conference Paper
What Kinds of Relational Features Are Useful for Statistical Learning?
A workmanlike, but nevertheless very effective combination of statistical and relational learning uses a statistical learner to construct models with features identified (quite often, separately) by a relation...
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Chapter and Conference Paper
Probing the Space of Optimal Markov Logic Networks for Sequence Labeling
Discovering relational structure between input features in sequence labeling models has shown to improve their accuracies in several problem settings. The problem of learning relational structure for sequence ...
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Chapter and Conference Paper
BET : An Inductive Logic Programming Workbench
Existing ILP (Inductive Logic Programming) systems are implemented in different languages namely C, Progol, etc. Also, each system has its customized format for the input data. This makes it very tedious and t...
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Chapter and Conference Paper
Pruning Search Space for Weighted First Order Horn Clause Satisfiability
Many SRL models pose logical inference as weighted satisfiability solving. Performing logical inference after completely grounding clauses with all possible constants is computationally expensive and approache...
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Chapter and Conference Paper
Parameter Screening and Optimisation for ILP Using Designed Experiments
Reports of experiments conducted with an Inductive Logic Programming system rarely describe how specific values of parameters of the system are arrived at when constructing models. Usually, no attempt is made ...
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Chapter and Conference Paper
Incorporating Linguistic Expertise Using ILP for Named Entity Recognition in Data Hungry Indian Languages
Develo** linguistically sound and data-compliant rules for named entity annotation is usually an intensive and time consuming process for any developer or linguist. In this work, we present the use of two In...
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Chapter and Conference Paper
Using ILP to Construct Features for Information Extraction from Semi-structured Text
Machine-generated documents containing semi-structured text are rapidly forming the bulk of data being stored in an organisation. Given a feature-based representation of such data, methods like SVMs are able t...
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Chapter and Conference Paper
Feature Construction Using Theory-Guided Sampling and Randomised Search
It has repeatedly been found that very good predictive models can result from using Boolean features constructed by an an Inductive Logic Programming (ILP) system with access to relevant relational information...
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Chapter and Conference Paper
Word Sense Disambiguation Using Inductive Logic Programming
The identification of the correct sense of a word is necessary for many tasks in automatic natural language processing like machine translation, information retrieval, speech and text processing. Automatic Wor...
