Massive Query Expansion by Exploiting Graph Properties Joan Guisado-Gámez Josep Lluís Larriba Pey David Domínguez Sal.

Slides:

Advertisements

Similar presentations

Dynamic Data Partitioning for Distributed Graph Databases Xavier Martínez Palau David Domínguez Sal Josep Lluís Larriba Pey.

Advertisements

CREATE THE DIFFERENCE Before you start Please press F5 to run this show.

Document Summarization using Conditional Random Fields Dou Shen, Jian-Tao Sun, Hua Li, Qiang Yang, Zheng Chen IJCAI 2007 Hao-Chin Chang Department of Computer.

R ESOLVING AND P ARAMETER E STIMATION OF N ON -S YNCHRONOUS S AMPLING P ULSE S IGNALS B ASED ON T AYLOR S ERIES E XPANSION Bo Wu National Mobile Communications.

P REDICTION OF NBA G AME P ACE Fa Wang. I NTRODUCTION Possession based NBA game prediction dominates What is Pace? Total score = ASPM (points/possession)

Creating a Similarity Graph from WordNet

Yiming Zhang SUNY at Buffalo TRAFFIC SIGN RECOGNITION WITH COLOR IMAGE.

H IDDEN C ONCEPT D ETECTION IN G RAPH - B ASED R ANKING A LGORITHM FOR P ERSONALIZED R ECOMMENDATION Nan Li Computer Science Department Carnegie Mellon.

D2I Modena, 27 Aprile 2001 Methodologies and techniques for the extraction, the representation and the integration of structured and semi-structured information.

Product Strategy A-team

ER 2002BYU Data Extraction Group Automatically Extracting Ontologically Specified Data from HTML Tables with Unknown Structure David W. Embley, Cui Tao,

CSE 300: Software Reliability Engineering Topics covered: Software metrics and software reliability.

By Loren Kessell en_New_Beetle_Germany.jpg.

Integrating Multiple Resources for Diversified Query Expansion Arbi Bouchoucha, Xiaohua Liu, and Jian-Yun Nie Dept. of Computer Science and Operations.

7/6/2015 Orthogonal Functions Chapter /6/2015 Orthogonal Functions Chapter 7 2.

Copyright © 2011 Pearson, Inc. 6.2 Dot Product of Vectors.

Volkswagen Volkswagen (VW) is a German automobile manufacturer headquartered in Wolfsburg, Lower Saxony, Germany. Established in 1937, Volkswagen is the.

The VW Beetle CESAR REIS LEIVA. Why the VW Beetle? Historical Relevance  1939 – 1945 : During the WWII, the automobile industry was composed only by.

Module 3- The Production Possibilities Curve

Information Retrieval in Practice

Latent Semantic Analysis Hongning Wang VS model in practice Document and query are represented by term vectors – Terms are not necessarily orthogonal.

M ULTIFRAME P OINT C ORRESPONDENCE By Naseem Mahajna & Muhammad Zoabi.

Xueyu(Sherry) Du Mechanical and Aerospace Engineering University of Florida 4/10/2014 ZENITH: A ROBOT THAT CAN AUTOMATICALLY CLIMB UP THE STAIRS.

S EMISUPERVISED M ULTIVIEW D ISTANCE M ETRIC L EARNING FOR C ARTOON S YNTHESIS Jun Yu, Meng Wang, Member, IEEE, and Dacheng Tao, Senior Member, IEEE.

Dr. Ali M. Hadianfard Paramedical School, AJUMS

Query Expansion By: Sean McGettrick. What is Query Expansion? Query Expansion is the term given when a search engine adding search terms to a user’s weighted.

D YNAMO : A MAZON ’ S H IGHLY A VAILABLE K EY - VALUE S TORE Presenters: Pourya Aliabadi Boshra Ardallani Paria Rakhshani 1 Professor : Dr Sheykh Esmaili.

A NSWERING C ONJUNCTIVE Q UERIES W ITH I NEQUALITIES Paris Koutris 1 Tova Milo 2 Sudeepa Roy 1 Dan Suciu 1 ICDT University of Washington 2 Tel Aviv.

Probabilistic Query Expansion Using Query Logs Hang Cui Tianjin University, China Ji-Rong Wen Microsoft Research Asia, China Jian-Yun Nie University of.

The roots of innovation Future and Emerging Technologies (FET) Future and Emerging Technologies (FET) The roots of innovation Proactive initiative on:

A S URVEY ON I NFORMATION E XTRACTION FROM D OCUMENTS U SING S TRUCTURES OF S ENTENCES Chikayama Taura Lab. M1 Mitsuharu Kurita 1.

Intellectual Property: Patent Eligible Subject Matter Prof. Peng

LATENT SEMANTIC INDEXING Hande Zırtıloğlu Levent Altunyurt.

IBM QBIC: Query by Image and Video Content Jianping Fan Department of Computer Science University of North Carolina at Charlotte Charlotte, NC 28223

Review Questions Jyun-Ming Chen Spring Wavelet Transform What is wavelet? How is wavelet transform different from Fourier transform? Wavelets are.

 (Worse) It is a fact that engineers select an appropriate variable and the transformed observations are treated as though they are normally distributed.

Contextual Ranking of Keywords Using Click Data Utku Irmak, Vadim von Brzeski, Reiner Kraft Yahoo! Inc ICDE 09’ Datamining session Summarized.

Contextual Ranking of Keywords Using Click Data ICDE`09 Utku Irmak Vadim von Brzeski Vadim von Brzeski Reiner Kraft.

Aspect-Oriented Requirements Engineering David Schaefer, Joao Araujo, Isabel Brito, Awais Rashid, Claudia Mesquita.

C OMMUNICATION I N THE WORK PLACE By: John Randle JR Class: interpersonal communication Teacher: Ignatjeva.

Query Expansion By: Sean McGettrick. What is Query Expansion? Query Expansion is the term given when a search engine adding search terms to a user’s weighted.

Competence Centre on Information Extraction and Image Understanding for Earth Observation 29th March 2007 Category - based Semantic Search Engine 1 Mihai.

CS532 TERM PAPER MEASUREMENT IN SOFTWARE ENGINEERING NAVEEN KUMAR SOMA.

Database Architecture Course Orientation & Context.

Precision Rectifier.

LATENT SEMANTIC INDEXING BY SINGULAR VALUE DECOMPOSITION

20 th Century Transportation, Globalization, Diversity Worldwide, what is the best selling motorized vehicle model of all time?

Content-Based Image Retrieval Using Block Discrete Cosine Transform Presented by Te-Wei Chiang Department of Information Networking Technology Chihlee.

Selecting Good Expansion Terms for Pseudo-Relevance Feedback Guihong Cao, Jian-Yun Nie, Jianfeng Gao, Stephen Robertson 2008 SIGIR reporter: Chen, Yi-wen.

Extracting Query Facets From Search Results Date : 2013/08/20 Source : SIGIR’13 Authors : Weize Kong and James Allan Advisor : Dr.Jia-ling, Koh Speaker.

S CALABLE S KYLINE C OMPUTATION U SING O BJECT - BASED S PACE P ARTITIONING Shiming Zhang Nikos Mamoulis David W. Cheung sigmod

Similarity Measurement and Detection of Video Sequences Chu-Hong HOI Supervisor: Prof. Michael R. LYU Marker: Prof. Yiu Sang MOON 25 April, 2003 Dept.

T HERMOELECTRIC G ENERATOR TEG Joanna Kubczak Agnieszka Smukała Marta Weiss.

L IFE - STAGE P REDICTION FOR P RODUCT R ECOMMENDATION IN E- COMMERCE Speaker: Jim-An Tsai Advisor: Jia-ling Koh Author: Peng Jiang, Yadong Zhu, Yi Zhang,

E XPANSION - R EFLECTION Laura Delascasas 8C. I NTRODUCTION We learnt in class that we can use the expansion method instead of long multiplications in.

Analysis and Optimization of Question Answering Systems David Dominguez Sal Director: Josep Lluis Larriba Pey.

Learn ETL tools for Accurate loading of data. ETL testing is very interesting and informative among the software testing tools. ETL is a process to testing.

CSCE 590 Web Scraping – Information Extraction II

Describing items from a catalogue

6.2 Dot Product of Vectors.

Information Retrieval on the World Wide Web

Section 2.5 Graphing Techniques; Transformations

“The Truth About Cats And Dogs”

Aim of the project Take your image Submit it to the search engine

Section 2.5 Graphing Techniques; Transformations

T H E P U B G P R O J E C T.

Determining the Function Obtained from a Series of Transformations.

Vibrational Spectroscopy of Liquid Carbon Probed by Chirped Coherent Anti-Stokes Raman Scattering (c-CARS) Paul Peng, Saykally Group, Department of Chemistry,

Software Development Tools Computer Aided Software Engineering

Presentation transcript:

Massive Query Expansion by Exploiting Graph Properties Joan Guisado-Gámez Josep Lluís Larriba Pey David Domínguez Sal

2/8 P ROBLEM IN I NFORMATION R ETRIEVAL Query = “colored Volkswagen beetles”

3/8 B RIEF I NTRODUCTION Process of transforming Q O into Q E Detect expansion features (terms/phrases) What kind of expansion features? How to obtain the expansion features?

4/8 T OPOLOGICAL Q UERY E XPANSION Query = “colored Volkswagen beetles” Context = “any model of Volkswagen beetles car of any color and year”

5/8 E XPANSION F EATURES Most important extension Features: “Volkswagen beetle”, “Volkswagen fusca”, “VW type 1”, “Volkswagen 1200”, “Volkswagen bug”, “Volkswagen super bug”, “VW bug”,”VW Käfer” “Volkswagen new Beetle” “Baja bug” “Volkswagen group”, “VW group” H-Shifter, engine, car, automobile,…. Query = “colored Volkswagen beetles”

6/8 S OME R ESULTS Query = “colored Volkswagen beetles”

7/8 C ONCLUSIONS Achieves good results allowing to identify new concepts. Precision improves up to 27% Orthogonal to linguistic techniques. Outperforms pseudo-relevance feedback techniques.

8/8 T HANK YOU