Physicians intuitively apply pattern recognition when evaluating a patient. Rational diagnosis making requires that clinical patterns be put in the context of disease prior probability, yet physicians often exhibit flawed probabilistic reasoning. Difficulties in making a diagnosis are reflected in the high rates of deadly and costly diagnostic errors. Introduced 6 decades ago, computerized diag...

This paper presents a system which learns to answer questions on a broad range of topics from a knowledge base using few handcrafted features. Our model learns low-dimensional embeddings of words and knowledge base constituents; these representations are used to score natural language questions against candidate answers. Training our system using pairs of questions and structured representation...

Intelligent text-oriented tools for representing and searching the biological research literature are being developed, which combine object-oriented databases with artificial intelligence techniques to create a richly structured knowledge base of Materials and Methods sections of biological research papers. A knowledge model of experimental processes, biological and chemical substances, and ana...

We present Mobipedia, an integrated knowledge base with information about 1 million mobile applications (apps) such as their category, meta-data (author, reviews, rating, release date), permissions and libraries used, and similar apps. The goal of Mobipedia is to integrate unstructured and semi-structured data about mobile apps from publicly available data sources and publish it as Linked Data ...

In recent years large repositories of structured knowledge (DBpedia, Freebase, YAGO) have become a valuable resource for language technologies, especially for the automatic aggregation of knowledge from textual data. One essential component of language technologies, which leverage such knowledge bases, is the linking of words or phrases in specific text documents with elements from the knowledg...

Knowledge bases and structured summaries are playing a crucial role in many applications, such as text summarization, question answering, essay grading, and semantic search. Although, many systems (e.g., DBpedia and YaGo2) provide massive knowledge bases of such summaries, they all suffer from incompleteness, inconsistencies, and inaccuracies. These problems can be addressed and much improved b...

Title of dissertation: WIKITOLOGY: A NOVEL HYBRID KNOWLEDGE BASE DERIVED FROM WIKIPEDIA Zareen Saba Syed, Doctor of Philosophy, 2010 Dissertation directed by: Professor Timothy W. Finin Department of Computer Science and Electrical Engineering World knowledge may be available in different forms such as relational databases, triple stores, link graphs, meta-data and free text. Human minds are ca...

The paper starts with a discussion of the roles an organisational memory (OM) should play and what kind of knowledge should go into it. We then identify two kinds of integration problems. The rst one is concerned with integrating the knowledge bases of diierent knowledge-based systems employed in an organisation into one physically or virtually uniied knowledge base which is to be considered as...

In this paper, we propose the first system, so-called Open Programming Knowledge Extraction (OPKE), to automatically extract knowledge from programming Question-Answering (QA) communities. OPKE is the first step of building a programming-centric knowledge base. Data mining and Natural Language Processing techniques are leveraged to identify duplicate questions and construct structured informati...