Question Answering Against Very-Large Text Collections
نویسندگان
چکیده
Question answering involves developing methods to extract useful information from large collections of documents. This is done with specialised search engines such as Answer Finder. The aim of Answer Finder is to provide an answer to a question rather than a page listing related documents that may contain the correct answer. So, a question such as"How tall is the Eiffel Tower"would simply return"325m"or"1,063ft". Our task was to build on the current version of Answer Finder by improving information retrieval, and also improving the pre-processing involved in question series analysis.
منابع مشابه
A combined IR/NLP approach to question answering against large text collections
We describe an approach to finding literal answer strings to natural language questions in large text collections. The approach involves linking an IR system with an NLP system that performs reasonably thorough linguistic analysis. The IR system treats the question as a query and returns a set of top ranked documents or passages. The NLP system parses the question and analyses the top ranked do...
متن کاملProcessing Definition Questions in an Open-Domain Question Answering System
This paper presents a hybrid method for finding answers to Definition questions within large text collections. Because candidate answers to Definition questions do not generally fall in clearly defined semantic categories, answer discovery is guided by a combination of pattern matching and WordNet-based question expansion. The method is incorporated in a large opendomain question answering syst...
متن کاملQuestion Answering from Large Document Collections
We present a question answering system with a hybrid design, combining techniques from knowledge representation, information retrieval, and natural language processing. This combination enables domain independence and robustness in the face of text variability, both in the question and in the raw text documents used as knowledge sources. We describe the specific design of our current prototype,...
متن کاملPassage Selection To Improve Question Answering
Open-Domain Question Answering systems (QA) performs the task of detecting text fragments in a collection of documents that contain the response to user’s queries. These systems use high complexity tools that reduce its applicability to the treatment of small amounts of text. Consequently, when working on large document collections, QA systems apply Information Retrieval (IR) techniques to redu...
متن کاملEvaluation of Information Access Technologies with Asian Languages at NTCIR Workshop
This paper introduces the NTCIR Workshop, a series of evaluation workshops that are designed to enhance research in information access technologies, such as information retrieval, cross-lingual information retrieval, text summarization, question answering and text mining, by providing infrastructure for large-scale evaluations. A brief history, the test collections, and tasks are described. To ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- CoRR
دوره abs/1304.7157 شماره
صفحات -
تاریخ انتشار 2013