Automatic Cross-Language Retrieval Using Latent Semantic Indexing

By Susan T. Dumais, Todd A. Letsche, Michael L. Littman, T. Landauer. 1997

How researchers see this paper

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

1. Jianfeng Gao
2. Yoshua Bengio
3. Li Deng
4. Mohit Bansal
5. Zhe Gan
6. Xiaodong He
7. Percy Liang
8. Dacheng Tao

Citations in the corpus

• Multi-Relational Latent Semantic Analysis (2013, background): “…proven successful in a wide variety of NLP and IR applications, such as document clustering (Xu et al., 2003) and cross-lingual document retrieval (Dumais et al., 1997; Platt et al., 2010) at the document level and sentential semantics (Guo and Diab, 2012; Guo and Diab, 2013) and syntactic…”
• Learning Continuous Phrase Representations for Translation Modeling (2014, background): “As a result, variants of such models for cross-lingual scenarios have been proposed so that words in different languages are projected into the shared latent vector space (Dumais et al. 1997; Platt et al. 2010; Vinokourov et al. 2002; Yih et al. 2011; Gao et al. 2011; Huang et al. 2013; Zou et al. 2”
• Learning Discriminative Projections for Text Similarity Measures (2011, methodology): “For CL-LSI, OPCA, and CCA, we include results from that work directly.”
• Latent Semantic Kernels (2001, methodology): “Keywords: Kernel methods, latent semantic indexing, latent semantic kernels, Gram-Schmidt kernels, text categorization”
• Semantic Matching in Search (2014, background): “These include collaborative filtering [101, 1, 2, 102, 45, 149, 9, 44], image annotation [83, 76, 159], paraphrasing and textual entailment [62, 54, 139, 203, 55, 85, 165, 35], question answering [37, 126, 21, 205, 178, 130], cross-language information retrieval [64, 141, 140], short text conversati”
• Learning Semantic Representations for the Phrase Translation Model (2013, background): “As a result, variants of such models for crosslingual scenarios have been proposed [7, 9, 22, 26] where documents in different languages are projected into the shared latent concept space.”
• WordICA—emergence of linguistic representations for words by independent component analysis (2010, background): “(1987), such as cross-language retrieval (Dumais et al. 1997), word sense disambiguation (Niu et al. 2004), text summarization (Steinberger et al. 2005), text segmentation (Choi, Wiemer-Hastings and Moore 2001), and measurement of textual coherence (Foltz, Kintsch and Landauer 1998).”
• Cross-Language Text Classification Using Structural Correspondence Learning (2010, methodology): “For instance, cross-language latent semantic indexing (Dumais et al., 1997) and cross-language explicit semantic analysis (Potthast et al.”
• Translingual Document Representations from Discriminative Projections (2010, methodology): “Cross-language Latent Semantic Indexing (CL-LSI) (Dumais et al., 1997) applied LSA to concatenated comparable documents from multiple languages.”