Concept

Tf–idf

Related publications (30)

Crosslingual Document Embedding as Reduced-Rank Ridge Regression

Martin Jaggi, Robert West, Martin Josifoski, Ivan Paskov

There has recently been much interest in extending vector-based word representations to multiple languages, such that words can be compared across languages. In this paper, we shift the focus from words to documents and introduce a method for embedding doc ...

2019

New Multi-Keyword Ciphertext Search Method for Sensor Network Cloud Platforms

Jiyong Zhang, Yue Wang, Hongyu Yang

This paper proposed a multi-keyword ciphertext search, based on an improved-quality hierarchical clustering (MCS-IQHC) method. MCS-IQHC is a novel technique, which is tailored to work with encrypted data. It has improved search accuracy and can self-adapt ...

MDPI2018

Using Networks to Visualize Publications

Dario Rodighiero

Retrieval systems are often shaped as lists organized in pages. However, the majority of users look at the first page ignoring the other ones. This presentation concerns an alterna- tive way to present the results of a query using network visualizations.  ...

2018

Text Similarity in Vector Space Models: A Comparative Study

Kenneth Younge, Omid Shahmirzadi, Adam Lugowski

Automatic measurement of semantic text similarity is an important task in natural language processing. In this paper, we evaluate the performance of different vector space models to perform this task. We address the real-world problem of modeling patent-to ...

2018

Cross-lingual Transfer for News Article Labeling: Benchmarking Statistical and Neural Models

Andrei Popescu-Belis, Nikolaos Pappas, Khalil Mrini

Cross-lingual transfer has been shown to increase the performance of a text classification model thanks to the use of Multilingual Hierarchical Attention Networks (MHAN), on which this work is based. Firstly, we compared the performance of monolingual and ...

Idiap2017

Question Answering in Conversations: Query Refinement Using Contextual and Semantic Information

Andrei Popescu-Belis, Maryam Habibi, Parvaz Mahdabi

This paper introduces a query refinement method applied to questions asked by users to a system during a meeting or a conversation that they have with other users. To answer the questions, the proposed method leverages the local context of the conversation ...

Idiap2016

Building Word Embeddings for Solving Natural Language Processing

Rémi Philippe Lebret

Word embedding is a feature learning technique which aims at mapping words from a vocabulary into vectors of real numbers in a low-dimensional space. By leveraging large corpora of unlabeled text, such continuous space representations can be computed for c ...

École Polytechnique Fédérale de Lausanne2016

Word Embeddings for Natural Language Processing

Rémi Philippe Lebret

EPFL2016

Keyword Extraction and Clustering for Document Recommendation in Conversations

Andrei Popescu-Belis, Maryam Habibi

This paper addresses the problem of keyword extraction from conversations, with the goal of using these keywords to retrieve, for each short conversation fragment, a small number of potentially relevant documents, which can be recommended to participants. ...

2015

Query Refinement Using Conversational Context: a Method and an Evaluation Resource

Andrei Popescu-Belis, Maryam Habibi

This paper introduces a query refinement method applied to queries asked by users during a meeting or a conversation. Current approaches suffer from poor quality to achieve this goal, but we argue that their performance could be improved by focusing on the ...

2015

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