TF is a desktop search engine with which you are able to combine full text search with selective searches around a regular structure of documents. Searches files by name, size, type, author, etc. Browses search results, highlights and navigates through words found in text. Supports Unicode, PDF, XLS, DOC, PPS, PPT, HTML, RTF, BMP, GIF, TIFF, PNG, JPEG, PSD and more. Searches and browses ZIP, RAR, MHT and CHM archives. Supports proximity searches.
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Text Filterer 3.4 Full Description:
Text Filterer is an advanced desktop full text searcher. With TF, you can instantly search for single words, partial words, Boolean word combinations, and exact or proximity phrases within hierarchically organized collections of documents. Classic Explorer-like interface allows you to easily browse a search result by folders, switch between found documents viewing their contents in the preview pane, and navigate through the found words highlighted in text. Search results can also be filtered by file name, type, location, date/time, size, title, author, etc. Search queries are stored as filters being usable across sessions. TF supports plain text, Unicode, RTF, XLS, HTML, PDF, and uses MS Word and PowerPoint to index DOC, WPD, PPS, PPT and other MS Word supported files. TF supports many image formats such as BMP, ICO, GIF, TIFF, PNG, JPEG, PSD, WMF and more. TF searches for Exif data embedded into JPEG and TIFF files. TF transparently works with ZIP, RAR, MHT and CHM archives treating them like folders. With group of Excel files having same columns, TF can selectively search by columns and rows presenting search results in one view. TF shows search results in the list view, with documents (or their parts called snippets) as rows, and their attributes as columns. Column data of a search result can be saved to a tab-delimited text file for later processing with a spreadsheet or database application. Resultant documents can be copied/extracted to a folder with or without conversion of them into plain-text copies. TF has support for multilingual texts. Advanced features include selective searches by used-defined data fields established around a common regular structure of documents, if any, and chopping documents into snippets to make them units of your searches instead of entire files, if they can be structurally subdivided into such snippets.
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