Semantic search : discover the Power of SOPHIA
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White Papers
White Papers
This is an index of White Papers authored by SOPHIA personnel. Click on a title to view a brief abstract of each paper.
In this paper we focus on one of the key differentiators between SOPHIA & other search technologies - the fact it is based on the recognised linguistical model called Semiotics. Semiotics is the scientific study of signs, symbols and text and includes how meaning is constructed and understood. The paper examines how SOPHIA leverages this model to provide context aware search & discovery within document corpora and highlights the benefits it brings over conventional approaches to search.
In this paper we look at 2 models of retrieval. The first is the conventional Boolean search approach whereby documents containing the query terms are returned as candidate documents. The other is semantic search where the search engine utilises additional background information, (e.g. a taxonomy), which it has at its disposal to try and understand more fully what the user is asking for in order to provide a more useful results set. We outline the limitations of these approaches and discuss how SOPHIA delivers user benefits.
This document examines the drawbacks of presenting search results as flat lists and outlines the main approach widely used to try and address some of these problems - namely organising information thematically.
In this paper we present some common criticisms of conventional search - specifically its inability to discover new information and to help users find semantically similar documents. We show that SOPHIA, because it is uniquely based on the linguistic model of Semiotics, can overcome these limitations and provide a truly intelligent search that does not rely on taxonomies or human guidance and input.
In this paper we examine the importance of being able to determine what documents are semantically similar to each other and what similar actually means. Like so many aspects of the SOPHIA technology it boils down to context - being able to understand this effectively is the key.
SOPHIA is an intelligent search and discovery tool on a number of levels. You can read more about SOPHIA's intelligent unearthing of themes which exist within corpora and its unparalleled semantic discovery processes in the white paper 3 The Power of Thematic Search. In this paper we discuss SOPHIA's revolutionary new approach to ranking and filtering of discovered information.
This paper highlights how SOPHIA's intelligent algorithms actually understand the true meaning of documents and can therefore present more informed and meaningful information to users to enable them make more informed decisions.
In this paper we review SOPHIA's unique Query By Example (QBE) function which enables a user to query a corpus with an exemplar document. Instead of specifying a small number of very precise key terms to convey what they are looking for, an existing document is used as an example of the type of information sought. SOPHIA uses this query document to identify the most useful themes relating to this example and facilitates access to relevant documents.
In this paper we review the enhanced functionality that the SOPHIA interface provides alongside its core semantic search capabilities. This includes:
- Saving interesting search results and marked documents to refer to again
- Sharing saved searches with colleagues
- Intelligently monitoring previous search results and alerting users to new highly relevant information as it is published
- Creating reports, exporting and integrating to other applications and data analytic toolsets.
The White Paper on SOPHIA Architecture is currently In Production and will be posted soon. To be alerted to an update please email info@sophiasearch.com. Thank you for visiting SOPHIA Search.