Functionality |
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Ideas Cloud | | | Natural Language Processing & Conversation | | | Sentiment Analysis |
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Natural Language Processing (NLP)
NLP is a form of human-to-computer interaction where the elements of human language, be it spoken or written, are formalized so that a computer can perform value-adding tasks based on that interaction. Autonomy's approach differs from standard NLP use in that it is still able to harness the power of IDOL's conceptual analysis.
Autonomy's NLP technology functions independently of linguistic restraints, giving Autonomy's software universal application possibilities anywhere in the world.
Key Benefits:
Enhanced Search through Conversation
Autonomy engages the users in many different conversation paths to help them disambiguate their result sets. By clustering the results according to concepts and parameters, and accessing the users' transactional and profile information to personalize the categorization, search results are meaningfully organized for quick filtering and decision making. Users can look to community insight to help find information, as well as rely on Autonomy's conceptual analytics to process the search results and continue the dialogue. In addition to offering all legacy tools like "Did you mean...?" to correct spelling errors, providing query suggestions as the user is typing into the search box, and offering facets according to content source type, Autonomy enhances the search experience using features such as:
Automatic Summarization
Autonomy automatically produces a brief summary of each piece of content that is returned for a query. It generates three different types of summaries:
Active Query Community Guidance (AQCG)
Instead of merely returning those users whose profiles indicate knowledge in the subject that was queried, AQCG returns and automatically clusters into communities those users who are most relevant to the queried person. For instance, if a user queried the name of the company's VP of Sales and he/she had been in frequent communication with client Z's finance and sales organizations at the time, two of the clusters that may appear as a result of the query would be employees in Z's finance department and the employees in Z's sales department, automatically organized into their respective communities.
User Behavior to Improve Relevancy

IDOL can incorporate all of the users' aforementioned enterprise 2.0 activities (i.e. social tagging, bookmarking) and users' content consumption behavior to improve and personalize relevancy. Expert behavior will have greater influence on the calculation by default. Documents they author, rank highly or have consumed recently will be positively affected. Since IDOL can monitor user's desktop activity, it can form user profiles of their current interests and expertise with great precision. IDOL can also adapt ranking of results so that documents that are consumed with great frequency following a certain query will be placed higher for subsequent queries relating to that same topic. This ranking can be adapted based on the behavior of the user, group or the entire enterprise community.
Business users and administrators are empowered to adjust the influence that each of these activities has on the relevance calculation, but users themselves can also individually adjust the influence of these factors per query. They can choose to search and rank documents based purely on IDOL's conceptual relevance calculation, on what the community deems relevant, on their implicit and explicit profiles, or some combination of the three.
Dynamic Faceted Navigation
IDOL automatically extracts entities for parametric filtering and navigation. A large set of entities are supported out-of-the-box, including SSN, credit card numbers, ticker symbols, places and names. When a user performs a query, results can be organized in a parametric hierarchy for guided navigation (parameters displayed to the user are adjustable by the business user and the administrator using the Autonomy Business Console). The parameters can also be derived from databases and other structured information, which in turn can be automatically merged with facets from unstructured content.
More importantly, users can easily merge multiple facets together to adjust their search criteria via drag-and-drop. There is no administrative involvement required to re-order, combine or remove facets during a search. For instance, if a search for "global warming" returned person facets (including Al Gore) and place facets (including Kyoto), users can simply drag the Al Gore parameter into the Kyoto parameter so that the newly formed facet of Al Gore + Kyoto will include documents that contain both parameters. In this way, users can determine the navigation hierarchy for ease of search.
By removing the administrative overhead of maintaining a hierarchy, organizations not only eliminate the costly exercise of developing a taxonomy, but also increase the likelihood of adoption since the hierarchy is dictated by the users themselves.
Ideas Cloud

Following a query, IDOL displays all the prominent concepts extracted from each document in the result set. These "ideas" are derived from analyzing the entire text of each document and are not dependent on subjective metatags. The larger and bolder "ideas" indicate the appearance of that concept in many documents in the results list. The user can use the ideas cloud to focus his/her search even further. Clicking on an idea will refresh the results list with a more specific context that contains that concept.
Persistent Term Highlighting
In their respective profiles, users can define concepts, terms, rules, etc. that represent information of their interest. These entities will get consistently highlighted in the retrieval result set, together with the default IDOL highlighting for the executed query.

Zero Results AQG
IDOL can certainly suggest queries for the user if they misspell the query text. However, IDOL goes beyond correcting mistyping and provides query guidance for correctly spelled queries that still return zero results. IDOL suggests similar, yet alternate concepts they can query, which are organized in a hierarchic cluster.
Conversational UIs
The Carousel Search user interface allows users to easily scroll through the results and quickly preview each content to gauge their relevancy. Moreover, the AQG function underneath the search query allows users to further refine their search results. The user has the option of clicking on the Open button at the bottom center of the window to also display search results in a conventional list alongside the carousel.


Forthcoming Events for Natural Language Processing (NLP)
Archived Events for Natural Language Processing (NLP)
Protect Webinar |
Promote Webinar |
Protect Webinar |
This is a selection of our forthcoming events, please visit our seminars page for more information.
Automatic Hyperlinks provided by IDOL Server
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This is a small selection of the Autonomy case studies available, please visit our publications site at http://publications.autonomy.com/ for more information.
Automatic Hyperlinks provided by IDOL Server
Functionality |
![]() ![]() |
Ideas Cloud | | | Natural Language Processing & Conversation | | | Sentiment Analysis |
![]() ![]() |