Implementation of the SMART Information Retrieval System

By Chris Buckley. 1985

Subfields: Information Retrieval & Search

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Information Retrieval & Search

1. Jimmy J. Lin
2. Peilin Yang
3. Matt Crane
4. Joel M. Mackenzie
5. Andrew Trotman
6. Hui Fang
7. Chris Kamphuis
8. Rodrigo Nogueira

Citations in the corpus

• The Use of MMR, Diversity-Based Reranking for Reordering Documents and Producing Summaries (1998, background): “Conventional IR systems rank and assimilate documents based on maximizing relevance to the user query [1, 5].”
• Text Classification Algorithms: A Survey (2019, background): “only used in information filtering systems. Bayesian inference networks employ recursive inference to propagate values through the inference network and return documents with the highest ranking [34]. [234] used vector space model with iterative refinement for filtering task. 7.1.3. Sentiment Analysis ”
• PlanetP: using gossiping to build content addressable peer-to-peer information sharing communities (2003, methodology): “Four of the collections, CACM, MED, CRAN, and CISI were previously collected and used by Buckley to evaluate Smart [3].”
• Question Answering from Frequently Asked Question Files: Experiences with the FAQ FINDER System (1997, methodology): “For the first stage of processing, FAQ FINDER uses standard information-retrieval technology, the public-domain SMART informationretrieval system (Buckley 1985), to perform the initial step of narrowing the focus to a small subset of the FAQ files.”
• Supporting Interoperability Between Open-Source Search Engines with the Common Index File Format (2020, background): “Academic information retrieval researchers often share their innovations in open-source search engines, a tradition that dates back to the SMART system in the mid 1980s [2].”
• Multi-Document Summarization By Sentence Extraction (2000, methodology): “The results reported in this paper are based on the use of the SMART search engine (Buckley, 1985) to compute cosine similarities (with a SMART weighting of lnn for both queries and passages), stopwords eliminated from the indexed data and stemming turned on.”
• Peer-to-peer information retrieval using self-organizing semantic overlay networks (2003, methodology): “Figure 17(a) supports our claim by showing pLSI’s performance with different underlying VSM baselines (see [2] for the term weighting schemes in parentheses).”
• The Lucene for Information Access and Retrieval Research (LIARR) Workshop at SIGIR 2017 (2017, background): “Œe IR community has a longstanding interest in sharing systems to support research, which can be traced back to the version of Cornell’s SMART system [7] from the mid 1980s.”