NDLI: On Horizontal and Vertical Separation in Hierarchical Text Classification

Please wait, while we are loading the content...

Advances in Formal Models of Search and Search Behaviour

Exploiting the Bipartite Structure of Entity Grids for Document Coherence and Retrieval

Total Recall: Blue Sky on Mars

The Effect of Document Order and Topic Difficulty on Assessor Agreement

A Simple and Effective Approach to Score Standardisation

Estimating Embedding Vectors for Queries

Learning to Rank User Queries to Detect Search Tasks

On Horizontal and Vertical Separation in Hierarchical Text Classification

Query Anchoring Using Discriminative Query Models

Exploring Urban Lifestyles Using a Nonparametric Temporal Graphical Model

A Utility Maximization Framework for Privacy Preservation of User Generated Content

Utilizing Knowledge Bases in Text-centric Information Retrieval

Efficient and Effective Higher Order Proximity Modeling

Classifying User Search Intents for Query Auto-Completion

A Reproducibility Study of Information Retrieval Models

The Impact of Fixed-Cost Pooling Strategies on Test Collection Bias

Analysis of the Paragraph Vector Model for Information Retrieval

Fast Feature Selection for Learning to Rank

From "More Like This" to "Better Than This"

Rank-at-a-Time Query Processing

EventMiner: Mining Events from Annotated Documents

Joint Estimation of Topics and Hashtag Relevance in Cross-Lingual Tweets

Collaborative Information Retrieval: Frameworks, Theoretical Models, and Emerging Topics

PDF: A Probabilistic Data Fusion Framework for Retrieval and Ranking

An Analysis of the Cost and Benefit of Search Interactions

Power Analysis for Interleaving Experiments by Means of Offline Evaluation

Unbiased Comparative Evaluation of Ranking Functions

End to End Long Short Term Memory Networks for Non-Factoid Question Answering

A Unified Energy-based Framework for Learning to Rank

Understanding the Message of Images with Knowledge Base Traversals

A Study of Document Expansion using Translation Models and Dimensionality Reduction Methods

Who Wants to Join Me?: Companion Recommendation in Location Based Social Networks

Temporal Query Expansion Using a Continuous Hidden Markov Model

Topic Set Size Design and Power Analysis in Practice

Learning to Rank with Labeled Features

Lexical Query Modeling in Session Search

Retrievability in API-Based "Evaluation as a Service"

A Topical Approach to Retrievability Bias Estimation

Embedding-based Query Language Models

Bag-of-Entities Representation for Ranking

Exploiting Entity Linking in Queries for Entity Retrieval

Estimating Retrieval Performance Bound for Single Term Queries

Nearest Neighbour based Transformation Functions for Text Classification: A Case Study with StackOverflow

Optimization Method for Weighting Explicit and Latent Concepts in Clinical Decision Support Queries

Cross-Language Microblog Retrieval using Latent Semantic Modeling

On Horizontal and Vertical Separation in Hierarchical Text Classification

Content Provider	ACM Digital Library
Author	Dehghani, Mostafa Azarbonyad, Hosein Kamps, Jaap Marx, Maarten
Abstract	Hierarchy is an effective and common way of organizing data and representing their relationships at different levels of abstraction. However, hierarchical data dependencies cause difficulties in the estimation of "separable" models that can distinguish between the entities in the hierarchy. Extracting separable models of hierarchical entities requires us to take their relative position into account and to consider the different types of dependencies in the hierarchy. In this paper, we present an investigation of the effect of separability in text-based entity classification and argue that in hierarchical classification, a separation property should be established between entities not only in the same layer, but also in different layers. Our main findings are the followings. First, we analyse the importance of separability on the data representation in the task of classification and based on that, we introduce "Strong Separation Principle" for optimizing expected effectiveness of classifiers decision based on separation property. Second, we present Significant Words Language Models (SWLM) which capture all, and only, the essential features of hierarchical entities according to their relative position in the hierarchy resulting in horizontally and vertically separable models. Third, we validate our claims on real world data and demonstrate that how SWLM improves the accuracy of classification and how it provides transferable models over time. Although discussions in this paper focus on the classification problem, the models are applicable to any information access tasks on data that has, or can be mapped to, a hierarchical structure.
Starting Page	185
Ending Page	194
Page Count	10
File Format	PDF
ISBN	9781450344975
DOI	10.1145/2970398.2970408
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-09-12
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Hswlm Swlm Hierarchical significant words language models Hierarchical text classification Language models Significant words language models
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Significant Words Representations of Entities

On Horizontal and Vertical Separation in Hierarchical Text Classification

Luhn Revisited: Significant Words Language Models

Hierarchical voting classification scheme for improving visual sign language recognition

Use of latent words language models in ASR: A sampling-based implementation

A pre-experiment on effects of horizontal and vertical touch displays on group work in card classification tasks

Vertical and horizontal transmission in language evolution1.

Key words: horizontal and vertical fdi, supply and demand uncertainty, sovereign risk.

THE RELATIONSHIP BETWEEN MODELS OF HORIZONTAL AND VERTICAL DIFFERENTIATION

On Horizontal and Vertical Separation in Hierarchical Text Classification

Similar Documents

Significant Words Representations of Entities

On Horizontal and Vertical Separation in Hierarchical Text Classification

Luhn Revisited: Significant Words Language Models

Hierarchical voting classification scheme for improving visual sign language recognition

Use of latent words language models in ASR: A sampling-based implementation

A pre-experiment on effects of horizontal and vertical touch displays on group work in card classification tasks

Vertical and horizontal transmission in language evolution1.

Key words: horizontal and vertical fdi, supply and demand uncertainty, sovereign risk.

THE RELATIONSHIP BETWEEN MODELS OF HORIZONTAL AND VERTICAL DIFFERENTIATION

On Horizontal and Vertical Separation in Hierarchical Text Classification