將説明您快速匯總、 高效地流覽和群集中你 textbase 的文檔。TextAnalyst
在 TextAnalyst 中實現的唯一的語言和神經網路技術的協同作用可確保高速度和準確性的非結構化文本分析。
Making correct decisions often
requires analyzing large volumes of textual information.
Researchers, analysts, magazine editors, venture capitalists,
lawyers, help desk specialists, and even students are faced by
various text analysis tasks.
Huge piles of information accumulate in numerous text repositories
held at news agencies, libraries, corporations, individual PCs, and
the Web. The amount of stored information proliferates at a
disastrous rate, and the human eyes and brain are increasingly
unable to meet the challenges of this growth. Mankind is searching
for intelligent electronic assistants to help with text analysis
One needs to:
Distill the meaning of a text in a concise form
View accurate summaries before plunging into full documents
Efficiently navigate through large textbases
Perform natural language information retrieval
These and many other tasks can be successfully tackled by
TextAnalyst, a unique software tool for semantic analysis,
navigation, and search of unstructured texts.
TextAnalyst will help you quickly summarize, efficiently
navigate, and cluster documents in your textbase. TextAnalyst can
provide you with the ability to perform semantic information
retrieval or focus your text exploration around a certain subject.
A synergy of unique linguistic and neural network technologies
implemented in TextAnalyst ensures high speed and accuracy in the
analysis of unstructured texts.
Distilling the meaning of a text - formation and export of an
accurate Semantic Network of the text or textbase. This network
concisely represents the meaning of a text and serves as a basis for
all further analysis.
Accurate summarization of texts - the quality of the summary
is provided by a balanced combination of linguistic and neural
network investigation methods. The size of the summary is controlled
through the semantic weight threshold.
Subject-focused text exploration - user-specified
dictionaries of excluded and included words allow the investigation
to focus on a chosen subject.
Efficient navigation through a textbase - the knowledge base
can be navigated with hyperlinks from concepts in the Semantic
Network to sentences in the documents that contain the considered
combination of concepts. Individual sentences are in turn
hyperlinked to those places in original texts where they have been
Explication of the text theme structure - a tree-like topic
structure representing the semantics of the investigated texts is
automatically developed. The more important subjects are placed
closer to the root of a tree.
Clustering of texts - breaking links representing weak relations
in the original Semantic Network enables clustering of the textbase.
Semantic information retrieval - natural language queries are
analyzed for semantically important words and all relevant sentences
from the textbase documents are retrieved. In addition, a subtree of
concepts related to the query is formed, which facilitates a simple
search refinement. A Semantic Network is a set of the most important
concepts from the text and the relations between these concepts
weighted by their relative importance.
Existing users of TextAnalyst include government offices,
consulting and law firms, medical centers, scientific organizations,
electronic book publishers, customer support centers, political
institutions, and even college students. Potential users: