Sus características son:
- Indexing support for common desktop file formats, and for commonly used TREC research collections (eg TREC CDs 1-5, WT2G, WT10G, GOV, GOV2, Blogs06).
- Many document weighting models, such as many parameter-free Divergence from Randomness weighting models, Okapi BM25 and language modelling.
- Conventional query language supported, including phrases, and terms occurring in tags.
- Handling full-text indexing of large-scale document collections, in a centralised architecture to at least 25 million documents.
- Modular and open indexing and querying APIs, to allow easy extension for your own applications and research.
- Active Information Retrieval research fed into the Open Source platform.
- Open Source (Mozilla Public Licence).
- Written in cross-platform Java - works on Windows, Mac OS X, Linux and Unix.
- Large user-base over 3 years of public release.
- Out-of-the box indexing of tagged document collections, such as the TREC test collections.
- Out-of-the box indexing for documents of various formats, such as HTML, PDF, or Microsoft Word, Excel and PowerPoint files.
- Indexing of field information, such as TITLE, H1, HTML tags information
- Indexing of position information on a word, or a block (e.g. a window of terms within a distance) level.
- Support for various encodings of documents (UTF), to facilitate multi-lingual retrieval.
- Highly compressed index disk data structures.
- Highly compressed direct file for efficient query expansion.
- Alternative faster single-pass indexing.
- Various stemming techniques supported, including the Snowball stemmer for European languages.
- Provides standard querying facilities, as well as Query Expansion (pseudo-relevance feedback)
- Can be applied in interactive applications, such as the included Desktop Search, or in a batch setting for research & experimentation.
- Provides many standard document weighting models, including upto 126 Divergence From Randomness (DFR) document ranking models, and other models such as Okapi BM25, language modelling and TF-IDF. The new DFRee DFR weighting model is also included, which provides robust performance on a range of test collections without the need for any paramter tuning or training.
- Advanced query language that supports boolean operators, +/- operators, phrase and proximity search, and fields.
- Provides a number of parameter-free DFR term weighting models for automatic query expansion, in addition to Rocchio's query expansion.
- Flexible processing of terms through a pipeline of components, such as stop-words removers and stemmers.