science

LGTE

LGTE is a science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand LGTE rather than just read about it. In short: Lucene Geographic and Temporal (LGTE) is an information retrieval tool developed at Technical University of Lisbon which can be used as a search engine or as evaluation system for information retrieval techniques for research purposes. The first implementation powered by LGTE was the search engine of DIGMAP, a project co-funded by the community programme eContentplus between 2006 and 2008, which was aimed to provide…

Key takeaways

LGTE belongs to science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect LGTE to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of LGTE from memory before moving on to harder problems.

Reference excerpt

Lucene Geographic and Temporal (LGTE) is an information retrieval tool developed at Technical University of Lisbon which can be used as a search engine or as evaluation system for information retrieval techniques for research purposes. The first implementation powered by LGTE was the search engine of DIGMAP, a project co-funded by the community programme eContentplus between 2006 and 2008, which was aimed to provide services available on the web over old digitized maps from a group of partners over Europe including several National Libraries. The tool LGTE is built in Java Programming Language around the Lucene library for full-text search and introduces several extensions for dealing with geographical and temporal information. The package also includes utilities for information retrieval evaluation, such as classes for handling CLEF/TREC (Cross Language Evaluation Forúm/Text Retrieval Conference) topics and document collections. Technically LGTE is a layer on the top of Lucene and provides an extended Lucene API to integrate several services like snippets generation, query expansion, and many others. The LGTE provides the chance to implement new probabilistic models. The API depends on a set of modifications at the Lucene level, originally created by the researchers of the University of Amsterdam in a software tool named Lucene-lm developed by the group of Information and Language Processing Systems (ILPS). At the time, the tool was tested with success for the Okapi BM25 model, and a multinomial language model, but also includes divergence from randomness models. The LGTE 1.1.9 and later versions also provide the possibility to isolate the index fields in different index folders. Another recent feature is the configuration of Hierarchic Indexes using foreign key fields. This gives the chance to create scores for example based on the text of the sentence combined with the general score of the entire page.

Features Provides Isolated Fields using different folders Provides Hierarchic indexes through foreign key fields Provides classes to parse documents using Yahoo PlaceMaker Provides a simple and effective abstraction layer on top of Lucene Supports integrated retrieval and ranking with basis on thematic, temporal and geographical aspects. Supports the Lucene standard retrieval model, as well as the more advanced probabilistic retrieval approaches. Supports Rochio Query Expansion. Provides a framework for IR evaluation experiments (e.g. handling CLEF/TREC topics). Includes a Java alternative to the trec_eval tool, capable of performing significance tests over pairs of runs. Includes a simple test application for searching over the Braun Corpus or the Cranfield Corpus.

Bibliography Jorge Machado, Bruno Martins, José Borbinha, Gilberto Pedrosa "LGTE: Sistema aberto de Recuperação de Informação Textual, Geográfica e Temporal", II JORNADAS SASIG, Évora, 2–4 November 2009. Jorge Machado, Bruno Martins, José Borbinha "Experiments with N-Gram Prefixes on a Multinomial Language Model versus Lucene’s off-the-shelf ranking scheme and Rocchio Query Expansion (TEL@CLEF Monolingual Task)", European Conference of Digital Libraries/Cross Language Evaluation Forum of Cross Language Evaluation Forum, Corfu Greece, 2009. Jorge Machado, Gilberto Pedrosa, José Borbinha "LGTE: Lucene Extensions for Geo-Temporal Information Retrieval", European Conference on Information Retrieval/Workshop for Geographic Information on the Internet, Toulouse, 2009 Jorge Machado, Gilberto Pedrosa, José Borbinha "User interface for a geo-temporal search service using DIGMAP components", in Springer LNCS proceedings of European Conference of Digital Libraries, Corfu Greece, 2009. Jorge Machado, Gilberto Pedrosa, José Borbinha "Experiments on a Multinomial Language Model versus Lucene’s off-the-shelf ranking scheme and Rochio Query Expansion (TEL@CLEF Monolingual Task) ", European Conference of Digital Libraries/in Springer LNCS proceedings of Cross Language Evaluation Forum, Ahrus, 2008.

External links LGTE: Lucene Extensions for Geo-Temporal Information Retrieval download lgte jar file

Worked examples

Example 1 — a first encounter with LGTE

Start with the simplest possible case. Write down what LGTE claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to LGTE before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about LGTE ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of LGTE

In research: LGTE appears in science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses LGTE in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: LGTE is common in secondary-school and first-year university syllabi. It links to neighbouring topics Cartography, so understanding it makes those chapters shorter.
In everyday life: Look for LGTE outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study LGTE in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what LGTE means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain LGTE out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is LGTE in simple terms?

Why does LGTE matter?

Because it connects several science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study LGTE?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on LGTE.