Hello,
We are using Lucene to index scientific articles. We are also using Luke to verify the fields and values we index.
One of the fields we index is the author field that consists of the authors that have written the scientific article (an example of such data is shown at the bottom of the email).
The most common search on the author field is the following:
"find all the authors whose last name starts with Cole and the first name starts with S"
We thought of a proximity search (we want to make sure we take the first name and not the middle name/initial) similar like that
"Author:cole* S*"~1 "Author:cole* AND Author:S*"~1
What we were expecting was: all the documents that contain authors whose last name starts with Cole and the first name start with S and those words are near (next to each other)
Unfortunately when we type that search through the Luke "search interface" we do not get the expansion of the
words when using the similarity at the same time
So my question:
1) Does Luke cannot deal with that ?
2) Is the query not properly structured to get what expected ? Which would be the correct one ?
If Luke cannot deal with that, when writing the query through the Java application, which would be the
query to be provided to get what expected ?
Do we need to use a query filter ?
Thanks a lot in advance for your help,
Mariella
_____________________________________________________________________________________________ E.g.
Below there are three examples of data we index and to be precise the information related to the Authors field.
The following is the information related to scientific articles that we index.
1) The Authors field consists of two authors
Title: Using Document Dimensions for Enhanced Information Retrieval
Authors: Jayasooriya, Thimala([EMAIL PROTECTED]); Manandhar, Suresha([EMAIL PROTECTED])
Affiliations: a. Department of Computer Science, University of York
Abstract (English): Conventional document search techniques are constrained by attempting to match individual keywords or phrases to source documents. Thus, these techniques miss out documents that contain semantically similar terms, thereby achieving a relatively low degree of recall. At the same time, processing capabilities and tools for syntactic and semantic analysis of language have advanced to the point where an index-time linguistic analysis of source documents is both feasible and realistic. In this paper, we introduce document dimensions, a means of classifying or grouping terms discovered in documents. Using an enhanced version of Jakarta Lucene[1], we demonstrate that supplementing keyword analysis with some syntactic and semantic information can indeed enhance the quality of information retrieval results.
Publisher: Springer-Verlag
Publication Type: Original Paper
ISSN: 0302-9743
ISBN: 3-540-23659-7
Book DOI: 10.1007/b101591
2) The Authors field consists of six authors
Title: Multilingual Retrieval Experiments with MIMOR at the University of Hildesheim
Authors: Hackl, Renéa; Kölle, Ralpha; Mandl, Thomasa([EMAIL PROTECTED]); Ploedt, Alexandraa; Scheufen, Jan-Hendrika; Womser-Hacker, Christaa
Affiliations: a. University of Hildesheim, Information Science, Marienburger Platz 22, D-31141 Hildesheim
Abstract (English): Fusion and optimization based relevance judgements have proven to be successful strategies in information retrieval. In this years CLEF campaign we applied these strategies to multilingual retrieval with four languages. Our fusion experiments were carried out using freely available software. We used the snowball stemmers, internet translation services and the text retrieval tools in Lucene and the new MySQL.
Publisher: Springer-Verlag
Publication Type: Original Paper
ISSN: 0302-9743
ISBN: 3-540-24017-9
Book DOI: 10.1007/b102261
3)
The Authors field consists of one author and only middle and first initial are provided
Title: Letter to the editor
Author: Coleman, S.S.a
Affiliations: a. Department of Orthopaedics, The University of Utah School of Medicine, 50 North Medical Drive, Salt Lake City, UT 84132, USA US
Abstract: No Abstract
Publisher: Springer-Verlag
Item Identifier: 10.1007/s002640000113
Publication Type: Article
ISSN: 0341-2695
