DEFINITION Presenting semi-structured text retrieval results refers to the fact that, in semi-structured text retrieval, results are not independent and a judgment on their relevance needs to take their presentation into account. For example, HTML/XML/SGML documents contain a range of nested sub-trees that are fully contained in their ancestor elements. As a result, semi-structured text retriev...

This paper introduces us the full-text search engine based on Lucene and full-text retrieval technology, including indexing and system architecture, compares the full-text search of Lucene with the String search retrieval’s response time, the experimental results show that the full text search of Lucene has faster retrieval speed.

The problem of representing text documents within an Information Retrieval system is formulated as an analogy to the problem of representing the quantum states of a physical system. Lexical measurements of text are proposed as a way of representing documents which are akin to physical measurements on quantum states. Consequently, the representation of the text is only known after measurements h...

Text Retrieval Conference (TREC), organised by National Institute for Standards and Technology (NIST), is a set of tracks that represent different areas of text retrieval. These tracks provide a way to measure systems progress in certain fields in text retrieval such as crosslanguage retrieval, retrieval filtering and genomics. We participated in the question answering track. The questions in t...

We develop an automatic text categorization approach and investigate its application to text retrieval. The categorization approach is derived from a combination of a learning paradigm known as instancebased learning and an advanced document retrieval technique known as retrieval feedback. We demonstrate the e ectiveness of our categorization approach using two real-world document collections f...

Phase III of the T I P S T E R project included three workshops for evaluating document detection (information retrieval) projects: the fifth, sixth and seventh Text REtrieval Conferences (TRECs). This work was co-sponsored by the National Institute of Standards and Technology (NIST), and included evaluation not only of the T I P S T E R contractors, but also of many information retrieval group...

Large-scale evaluation initiatives, such as Text REtrieval Conference (TREC) in the United States, the CrossLanguage Evaluation Forum (CLEF) in Europe, and the NIINACSIS Test Collection for IR Systems (NTCIR) in Asia, contribute significantly to advancements in research and industrial innovation in the information retrieval sector, and to the building of strong research communities. A study con...

This paper is a personal take on the history of evaluation experiments in information retrieval. It describes some of the early experiments that were formative in our understanding, and goes on to discuss the current dominance of TREC (the Text REtrieval Conference) and to assess its impact.

ÐWe develop an automatic text categorization approach and investigate its application to text retrieval. The categorization approach is derived from a combination of a learning paradigm known as instance-based learning and an advanced document retrieval technique known as retrieval feedback. We demonstrate the effectiveness of our categorization approach using two realworld document collections...

The number of participating systems has grown from 25 in TREC-1 to 36 in TREC-4 (see Table 1), including most of the major text retrieval software companies and most of the universities doing research in text retrieval. The diversity of the participating groups has ensured that TREC represents many different approaches to text retrieval, while the emphasis on individual experiments evaluated wi...