Text documents are complex high dimensional objects. To effectively visualize such data it is important to reduce its dimensionality and visualize the low dimensional embedding as a 2-D or 3-D scatter plot. In this paper we explore dimensionality reduction methods that draw upon domain knowledge in order to achieve a better low dimensional embedding and visualization of documents. We consider t...

Aalto University, P.O. Box 11000, FI-00076 Aalto www.aalto.fi Author Mari-Sanna Paukkeri Name of the doctoral dissertation Languageand domain-independent text mining Publisher School of Science Unit Department of Information and Computer Science Series Aalto University publication series DOCTORAL DISSERTATIONS 137/2012 Field of research Computer and Information Science Manuscript submitted 4 Ma...

Most existing cross-domain recommendation algorithms focus on modeling ratings, while ignoring review texts. The review text, however, contains rich information, which can be utilized to alleviate data sparsity limitations, and interpret transfer patterns. In this paper, we investigate how to utilize the review text to improve cross-domain collaborative filtering models. The challenge lies in t...

This paper describes a general framework for measuring text reuse. This term is used to describe how content from a single or multiple number of known sources can be reused either verbatim (word-for-word copy) or otherwise rewritten depending upon factors influencing the creation of a new document. These may include reduction/ increase in length, change of style, simplification of content, shif...

We will demonstrate SconeEdit, a new tool for exploring and editing knowledge bases (KBs) that leverages interaction with domain texts. The tool provides an annotated view of user-selected text, allowing a user to see which concepts from the text are in the KB and to edit the KB directly from this Text View. Alongside the Text View, SconeEdit provides a navigable KB View of the knowledge base, ...

This paper describes a method for linear text segmentation which is twice as accurate and over seven times as fast as the state-of-the-art (Reynar, 1998). Inter-sentence similarity is replaced by rank in the local context. Boundary locations are discovered by divisive clustering.

This paper discusses a consistency in patterns of language use across domain-specific collections of text. We present a method for the automatic identification of domain-specific keywords – specialist terms – based on comparing language use in scientific domain-specific text collections with language use in texts intended for a more general audience. The method supports automatic production of ...

In this paper, we describe ontology-based text categorization in which the domain ontologies are automatically acquired through morphological rules and statistical methods. The ontology-based approach is a promising way for general information retrieval applications such as knowledge management or knowledge discovery. As a way to evaluate the quality of domain ontologies, we test our method thr...

In many knowledge intensive applications, it is necessary to have extensive domain-specific knowledge in addition to general-purpose knowledge bases. This paper presents a methodology for discovering domain-specific concepts and relationships in an attempt to extend WordNet. The method was tested on five seed concepts selected from the financial domain: interest rate, stock market, inflation, e...

An information extraction system is designed to operate over a specific domain, and cannot be applied to new domains without being adapted if it is to perform well. We will investigate the problem of adapting information extraction systems to new domains by first defining the task of information extraction and giving an example of an information extraction system. We will then outline the modul...