Context-Aware Search

Ideally, Queries and Searches of journal memoirs should retrieve all the you want to see and only the information you want to see. Retrieved information should be assembled and presented based on its relevance to the context and concepts of your query. Because Now & Then searches only through your lifetime of journal entries, it learns about your perspectives and personal knowledge. It uses this focused understanding to interpret the content and context of your queries while easily resolving ambiguities.

Over your life, you constantly add an ever greater amount of journal information. The seemingly vast amount of memoirs accumulated over your lifetime is actually a bounded, well mapped information domain. Your journal accommodates a significant increase in information storage as your your memoirs accumulate and your interests, ideas, activities, and relationships change.

Because your memoirs are finite and recorded from only your perspective, this finite and limited information is readily managed. Using machine learning, feedback, personalization, and your system training, Now & Then becomes familiar with all aspects of your
memoirs and adept and accurate in its searches.

Information preparation and organization
Although you may organize and structure your journal information (at entry or a later time), Now & Then breaks down and "parses" your entries into basic elements of words, phrases, sentences, paragraphs, and dates.

Once reduced to these "elements", misspellings, and alternative spellings and synonyms are identified using both system and user-managed thesauruses. The information is then indexed and modeled according to your personalized term scaling and knowledge maps.

Your journal's search engine uses these indexes and information models to understand each Query's content and context and to retrieve all and only the information you are looking for.

Also see Product Features:
Search & Query   ▪   Language indexing & Search   ▪   Knowledge-based indexing & search

home