1<!DOCTYPE html> 2<html lang="en"> 3 4 5<head> 6 7 <meta charset="utf-8"> 8 <meta http-equiv="X-UA-Compatible" content="IE=edge"> 9 <meta name="viewport" content="width=device-width, initial-scale=1"> 10 <meta name="description" content="Cayman is a clean, responsive theme for GitHub Pages.""> 11 <meta property=" og:image" content="https://kdd-milets.github.io/milets2022/assets/img/thumbnail.jpg"> 12 <meta property="og:type" content="website" /> 13 <meta property="og:title" content="KEIR@ECIR 2024: The First Workshop on Knowledge-Enhanced Information Retrieval"> 14 <meta property="og:description" content="KEIR@ECIR 2024: The First Workshop on Knowledge-Enhanced Information Retrieval"> 15 16 17 <title>KEIR@ECIR 2024: The First Workshop on Knowledge-Enhanced Information Retrieval</title> 18 19 <!-- Bootstrap Core CSS --> 20 <link href="assets/css/bootstrap.min.css" rel="stylesheet"> 21 22 <!-- Custom CSS --> 23 <link href="assets/css/agency.css?v=3" rel="stylesheet"> 24 25 <!-- Custom Fonts --> 26 <link href="assets/css/font-awesome.min.css" rel="stylesheet" type="text/css"> 27 <link href="https://fonts.googleapis.com/css?family=Montserrat:400,700" rel="stylesheet" type="text/css"> 28 <link href='https://fonts.googleapis.com/css?family=Kaushan+Script' rel='stylesheet' type='text/css'> 29 <link href='https://fonts.googleapis.com/css?family=Droid+Serif:400,700,400italic,700italic' rel='stylesheet' 30 type='text/css'> 31 <link href='https://fonts.googleapis.com/css?family=Roboto+Slab:400,100,300,700' rel='stylesheet' type='text/css'> 32 33 <!-- Global site tag (gtag.js) - Google Analytics -->
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59 60<nav class="navbar navbar-default navbar-fixed-top"> 61 <div class="container"> 62 <!-- Brand and toggle get grouped for better mobile display --> 63 <div class="navbar-header page-scroll"> 64 <button type="button" class="navbar-toggle" data-toggle="collapse" data-target="#bs-example-navbar-collapse-1"> 65 <span class="sr-only">Toggle navigation</span> 66 <span class="icon-bar"></span> 67 <span class="icon-bar"></span> 68 <span class="icon-bar"></span> 69 </button> 70 71 </div> 72 73 <!-- Collect the nav links, forms, and other content for toggling --> 74 <div class="collapse navbar-collapse" id="bs-example-navbar-collapse-1"> 75 <ul class="nav navbar-nav navbar-right"> 76 <li class="hidden"> 77 <a href="#page-top"></a> 78 </li> 79 <li> 80 <a class="page-scroll" href="#about">About</a> 81 </li> 82 <li> 83 <a class="page-scroll" href="#call">Call for Papers</a> 84 </li> 85 <li> 86 <a class="page-scroll" href="#dates">Important Dates</a> 87 </li> 88 <li> 89 <a class="page-scroll" href="#speaker">Keynotes</a> 90 </li> 91 <li> 92 <a class="page-scroll" href="#contributions">contributions</a> 93 </li> 94 <li> 95 <a class="page-scroll" href="#schedule">Schedule</a> 96 </li> 97 <li> 98 <a class="page-scroll" href="#organizer">Organizer</a> 99 </li> 100 <li> 101 <a class="page-scroll" href="#contact">Contact</a> 102 </li> 103 </ul> 104 </div> 105 <!-- /.navbar-collapse --> 106 </div> 107 <!-- /.container-fluid --> 108</nav> 109 110 111 <!-- Header --> 112 <header> 113 <div class="container"> 114 <div class="intro-text" style="color:white;"> 115 116 <div class="intro-heading">KEIR@ECIR 2024: The First Workshop on Knowledge-Enhanced Information Retrieval</div> 117 <div class="intro-lead-in"> on the 46th European Conference on Information Retrieval (ECIR'24) 118 </div> 119 <div class="intro-lead-in"> Glasgow, Scotland: 28th March, 2024 120 </div> 121 </div> 122 </div> 123 </header> 124 125 <section id="about" style="padding-top: 30px;" class=bg-mid-gray> 126 <div class="container"> 127 <div class="row"> 128 <div class="col-lg-12 text-center"> 129 <h2 class="section-heading">About the workshop</h2> 130 <!--h3 class="section-subheading text-muted">Lorem ipsum dolor sit amet consectetur.</h3--> 131 </div> 132 </div> 133 <div class="row text-justify"> 134 <div class="col-md-12"> 135 <p class="large text-muted"> 136 In the field of information retrieval (IR), harnessing knowledge from external knowledge bases, such 137 as Knowledge Graphs and Wikipedia, has emerged as a promising avenue for improving the effectiveness 138 and the interpretability of IR systems. These external knowledge bases offer valuable information 139 that empowers IR models to make more accurate predictions. The infusion of external knowledge bases 140 into IR models can provide enhanced ranking results and greater interpretability, offering 141 substantial advancements in the field. 142 <br><br> 143 The First Knowledge-Enhanced Information Retrieval workshop (KEIR @ ECIR 2024) will serve as a 144 platform to bring together researchers from academia and industry to explore and discuss various 145 aspects of knowledge-enhanced information retrieval systems, such as models, techniques, data 146 collection and evaluation. The workshop aims to not only deliberate upon the advantages and hurdles
147 intrinsic to the development of knowledge-enhanced PLMs, IR models and RecSys models but also to 148 facilitate in-depth discussions concerning the same. 149 </p> 150 151 <!-- <ul class="large text-muted"> 152 <li>Time series pattern mining and detection, representation, searching and indexing, classification, clustering, prediction, forecasting, and rule mining. 153 </li> 154 <li>Time series with special structure: spatiotemporal (e.g., traffic speeds at different locations), relational (e.g., patients with similar diseases), hierarchical, etc. 155 </li> 156 <li>Time series with sparse or irregular sampling, missing values at and not at random, and special types of measurement noise or bias. 157 </li> 158 <li>Time series that are multivariate, high-dimensional, heterogeneous, etc., or that possess other atypical properties. 159 </li> 160 <li>Time series analysis using less traditional approaches, such as deep learning and subspace clustering.</li> 161 <li>Privacy preserving time series mining and learning.</li> 162 <li>Online, high-speed learning and mining from streaming time series.</li> 163 <li>Uncertain time series mining.</li> 164 <li>Applications to high impact or relatively new time series domains, such as health and medicine, road traffic, and air quality. 165 </li> 166 <li>New, open, or unsolved problems in time series analysis and mining. 167 </li> 168 </ul> --> 169 </div> 170 </div> 171 </div> 172</section> 173 <section id="call" class=> 174 <div class="container"> 175 <div class="row"> 176 <div class="col-lg-12 text-center"> 177 <h2 class="section-heading">Call for Papers</h2> 178 </div> 179 </div> 180 <div class="row text-justify"> 181 <div class="col-md-12"> 182 <p class="large text-muted"> 183 This workshop holds a steadfast commitment to fostering collaboration among researchers engaged 184 in the realm of knowledge integration for IR, RecSys and NLP. We invite submissions regarding different 185 aspects of knowledge-enhanced information retrieval systems. Relevant topics include, but are not limited to: 186 </p> 187 <ul class="large text-muted"> 188 <ul> 189 <li>Knowledge-enhanced information retrieval models. </li> 190 <li>Knowledge-enhanced approaches for query processing, including query parsing, query expansion, 191 relevance feedback, and query reformulation. </li> 192 <li>Knowledge-enhanced recommendation models. </li> 193 <li>Knowledge-enhanced language models for retrieval. </li> 194 <li>Data augmentation for knowledge-enhanced information retrieval. </li> 195 <li>Knowledge retrieval from unstructured data and structured data. </li> 196 <li>Applications of knowledge-enhanced retrievals, such as dialogue systems, question answering, 197 summarisation and other domain-specific applications.</li> 198 <li>Data collection for knowledge-enhanced information retrieval.</li> 199 <li>Evaluation methodologies for knowledge-enhanced retrieval.</li> 200 <li>The interpretability and analysis of knowledge-enhanced models for IR, including potential biases and 201 ethical considerations.</li> 202 </ul> 203 </ul> 204 <p class="large text-muted"> 205 206 We invite authors to submit papers written in English. Submissions may range in length from a minimum of 6 207 pages to a maximum of 12 pages; however, references and supplementary materials may exceed this page count 208 without limitation. In order to facilitate a double-blind review process, authors must ensure that submissions 209 are fully anonymized. Please note that we do not impose a specific anonymity period prior to submission. 210 211 </br> </br> 212 The papers (.pdf format) should be submitted using the EasyChair submission system at <a 213 href="https://easychair.org/conferences/?conf=keirecir2024">https://easychair.org/conferences/?conf=keirecir2024</a>. 214 Authors should consult Springerâs authorsâ 215 guidelines and use their proceedings templates to prepare the submission. The Microsoft Word and LaTeX 216 versions of the template can be found at <a 217 href="https://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines">https://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines</a>. 218 Submissions to 219 KEIR@ECIR2024 will be peer-reviewed on the basis of technical qual
219ity, relevance to workshop topics, 220 originality, significance, clarity, etc. 221 </br> 222 223 We accept submissions of the following types: 224 </p> 225 <ul> 226 <li>Original work that is not published or submitted elsewhere.</li> 227 <li>Work that is submitted elsewhere and is still under review. In this case, the authors should make sure 228 that you are not violating the submission guidelines and anonymity requirements of the other venue(s). 229 </li> 230 <li>Work that has been rejected at ECIR 2024.</li> 231 </ul> 232 </br> 233 <p class="large text-muted"> 234 The proceedings of the KEIR workshop will be non-archival in nature. Extended versions of selected papers will 235 be recommended for special issues of several SCI-indexed international journals. However, authors retain the 236 right to submit their work to other peer-reviewed venues for further dissemination. 237 238 </p> 239 240 </div> 241 </div> 242 </div> 243</section> 244 <!DOCTYPE html> 245<html> 246 247<head> 248 <style> 249 del { 250 text-decoration: line-through; 251 /* æ·»å æ¨ªçº¿ */ 252 color: rgba(128, 128, 128, 0.5); 253 /* è®¾ç½®ææ¬é¢è² */ 254 } 255 256 .extended-date { 257 color: red; 258 /* è®¾ç½®ææ¬é¢è²ä¸ºçº¢è² */ 259 } 260 </style> 261</head> 262 263<body> 264 <section id="dates" class=bg-mid-gray> 265 <div class="container"> 266 <div class="row"> 267 <div class="col-lg-12 text-center"> 268 <h2 class="section-heading">Important Dates</h2> 269 <!--h3 class="section-subheading text-muted">Lorem ipsum dolor sit amet consectetur.</h3--> 270 </div> 271 </div> 272 <div class="row text-justify"> 273 <div class="col-md-12"> 274 <ul class="large text-muted"> 275 <li><b>Paper Submission Deadline (extended):</b><del> January 12, 2024 </del> <span 276 class="extended-date"></span><b>January 26, 277 2024, 11:59 PM, AoE</b></span></li> 278 <li><b>Acceptance Notification:</b> February 22, 2024 (11:59 PM, AoE)</li> 279 <li><b>Workshop Date:</b> March 28, 2024</li> 280 </ul> 281 </div> 282 </div> 283 </div> 284 </section> 285</body> 286 287</html> 288 <section id="speaker" class=> 289 <div class="container"> 290 <div class="row"> 291 <div class="col-lg-12 text-center"> 292 <h2 class="section-heading">Keynote Speakers </h2> 293 <!-- <h3>TBD</h3> --> 294 </div> 295 296 </div> 297 298 299 300 <div class="row speakers" class=> 301 <div class="col-sm-4"> 302 <div class="team-member"> 303 <a href="https://renzhaochun.github.io/" target="_blank"> 304 <img 305 src="assets/img/zhaochun_ren.png" 306 style="height: 240px; width: 240px" 307 class="img-responsive img-circle" 308 alt="Zhaochun Ren" 309 /> 310 </a> 311 <h4> 312 <a href="https://renzhaochun.github.io/" target="_blank" 313 >
313Zhaochun Ren</a 314 > 315 </h4> 316 <p class="text-muted"> 317 Associate professor<br />Leiden University, The Netherlands 318 </p> 319 </div> 320 </div> 321 322 <div class="col-sm-8 text-justify"> 323 <h4>Knowledge-enhanced Conversational Recommender Systems</h4> 324 <p><b>Abstract</b><br>Conversational Recommender Systems (CRS) have revolutionized how we interact with the recommender by discerning user preferences through iterative dialogues. However, the effectiveness of these systems is often hindered by a need for more contextual understanding for precise preference modeling. Integrating various external knowledge sources offers promising solutions to enrich dialogue context, predict user preferences, and generate informative responses. This presentation will delve into recent advancements in the realm of knowledge-enhanced CRS, spotlighting studies that leverage knowledge to refine recommendations and enrich user interactions. I will share insights from our recent research that bolsters the recommendation quality and the informativeness of conversational responses. Additionally, I will illuminate emerging research trajectories within this domain, emphasizing the synergy between CRS and Large Language Models.</p> 325 <p> 326 <b>Bio</b><br /> 327 Dr. Zhaochun Ren is an Associate Professor at Leiden University, the Netherlands. He is interested in information retrieval and natural language processing, with an emphasis on conversational artificial intelligence, recommender systems, and social media analysis. He aims to develop intelligent agents that can address complex user requests and solve core challenges in NLP and IR towards that goal. 328 </p> 329 </div> 330</div> 331 332 333 <div class="row speakers" class=> 334 <div class="col-sm-4"> 335 <div class="team-member"> 336 <a href="https://www.linkedin.com/in/ridhoreinanda/" target="_blank"> 337 <img 338 src="assets/img/Ridho_Reinanda.jpeg" 339 style="height: 240px; width: 240px" 340 class="img-responsive img-circle" 341 alt="Ridho Reinanda" 342 /> 343 </a> 344 <h4> 345 <a href="https://www.linkedin.com/in/ridhoreinanda/" target="_blank" 346 >Ridho Reinanda</a 347 > 348 </h4> 349 <p class="text-muted"> 350 AI Research Scientist<br />Bloomberg, UK 351 </p> 352 </div> 353 </div> 354 355 <div class="col-sm-8 text-justify"> 356 <h4>Utilizing Structured and Encoded Knowledge for Search</h4> 357 <p><b>Abstract</b><br>At Bloomberg, we build search applications for financial professionals as a part of our main product, the Bloomberg Terminal. In this talk, we will provide an illustration of a typical search workflow at Bloomberg, and discuss 1) how structured and encoded knowledge could be utilized end-to-end in a search system, and 2) challenges in applying them effectively at each step. Early in the pipeline, knowledge can be used to enrich and organize documents in the searchable collection. Thus, we start by discussing the document understanding step. Then, we consider the challenges of interpreting queries correctly and applying the appropriate retrieval configuration needed to satisfy the userâs information needs. We then continue to discuss the utilization of such enriched knowledge for document retrieval and reranking. Lastly, since user experience (UX) plays an important role in the search process, we will also discuss open questions around designing the user experience that is guided by knowledge.</p> 358 <p> 359 <b>Bio</b><br /> 360 Dr. Ridho Reinanda is an AI Research Scientist who is currently leading the Knowledge Graph team at Bloomberg. He obtained his Ph.D. in Information Retrieval at the University of Amsterdam, where he focused on leveraging knowledge graphs for information retrieval tasks and applying IR techniques for knowledge graph maintenance. 361 </p> 362 </div> 363</div> 364 365 366 367 368 </div> 369 370</section> 371 <section id="contributions" class=bg-mid-gray> 372 <div class="container"> 373 <div class="row"> 374 <div class="col-lg-12 text-center"> 375 <h2 class="section-heading">Contributions</h2> 376 </div> 377 </div> 378 <div class="text-center"> 379 <h3>Invited Talks</h3> 380 </div> 381 <div class="row text-justify"> 382 <div class="col-md-12"> 383 <ul class="large text-muted"> 384 <li><b>(1) Leveraging Entities and Knowledge Graph Semantics for Neural IR</b><br> 385 Shubham Chatterjee - University of Edinburgh</li> 386 </ul> 387 <ul class="large text-muted"> 388 <li><b>(2) Automatic Data Annotation and Webly Supervised Visual Question Answering</b><br> 389 Paul Lerner - Sorbonne Université, CNRS, ISIR</li> 390 </ul> 391 <ul class="large text-muted"> 392 <li><b>(3) Leveraging Contrastive Learning and Noise Augmentation for Effective Knowledge Graph-driven 393 Recommendation 394 </b><br> 395 Zeyuan Meng - University of Glasgow</li> 396 </ul> 397 <ul class="large text-muted"> 398 <li><b>(4) Enhancing event-specific information retrieval by knowledge graphs</b><br>Sara Abdollahi - Leibniz 399 University Hannover</li> 400 </ul> 401 <ul class="large text-muted"> 402 <li><b>(5) Adhoc Retrieval using Relevance Knowledge from a Query-Document Graph</b><br>Erlend Frayling - 403 University of Glasgow</li> 404 </ul> 405 </div> 406 </div> 407 408 <div class="text-center"> 409 <h3>Accepted Papers</h3> 410 </div> 411 <div class="row text-justify"> 412 <div class="col-md-12"> 413 <ul class="large text-muted"> 414 <li><b>(1) <a href="assets/files/keir_1.pdf">Adaptive Latent Entity Expansion for Document Retrieval 415 </a></b><br> 416 Iain Mackie, Shubham Chatterjee, Sean MacAvaney and Jeffrey Dalton </li> 417 </ul> 418 <ul class="large text-muted"> 419 <li><b>(2)<a href="assets/files/keir_2.pdf"> Satisfactory Medical Consultation based on Terminology-Enhanced 420 Information Retrieval and Emotional 421 In-Context Learning </a></b><br>
422 Jing Tang, Kaiwen Zuo, Hanbing Qin, Binli Luo and Shiyan Tang </li> 423 </li> 424 </ul> 425 <ul class="large text-muted"> 426 <li><b>(3) <a href="assets/files/keir_4.pdf">Enhancing Late Interaction with Informative Entities for Passage 427 Retrieval</a> 428 </b><br> 429 Jinyuan Fang, Zaiqiao Meng and Craig Macdonald </li> 430 </ul> 431 <ul class="large text-muted"> 432 <li><b>(4) <a href="assets/files/keir_3.pdf">Identifying User Shopping Needs in Voice Product Questions 433 for Proactive Shopping Recommendations 434 </a> 435 </b><br> 436 Besnik Fetahu, Nachshon Cohen, Elad Haramaty, Liane Lewin-Eytan, Oleg Rokhlenko and Shervin Malmasi</li> 437 </li> 438 </ul> 439 440 </div> 441 </div> 442 </div> 443</section> 444 <style> 445 table, 446 th, 447 td { 448 border: 1px solid black; 449 margin-left: auto; 450 margin-right: auto; 451 margin-top: auto; 452 margin-bottom: auto; 453 font-size: large; 454 } 455 456 th { 457 background-color: #009879; 458 color: #ffffff; 459 text-align: center; 460 } 461</style> 462<section id="schedule" class=> 463 <div class="container"> 464 <div class="row"> 465 <div class="col-lg-12 text-center"> 466 <h2 class="section-heading">Workshop Schedule</h2> 467 <!-- <h3>TBD</h3> --> 468 <!--h3 class="section-subheading text-muted">Lorem ipsum dolor sit amet consectetur.</h3--> 469 </div> 470 </div> 471 <table style="width: 100%"> 472 <tr> 473 <th width=130px> Activity type </th> 474 <th width=150px> Time </th> 475 <th width=400px> Activity </th> 476 </tr> 477 <tr> 478 <td width=130px> Opening remarks </td> 479 <td width=150px> 9:00 - 9:15 </td> 480 <td></td> 481 </tr> 482 <tr> 483 <td width=130px>Keynote I</td> 484 <td width=150px>9:15 - 10:05</td> 485 <td width=400px>Keynote I by Dr. Ridho Reinanda (45 min Talk + 5 min Q&A)</td> 486 </tr> 487 <tr> 488 <td width=130px>Invited talks</td> 489 <td width=150px>10:05 - 10:30</td> 490 <td width=400px>Invited talk by (1) Shubham Chatterjee (20 min Talk + 5 min Q&A)</td> 491 </tr> 492 <tr> 493 <td width=130px>Coffee break</td> 494 <td width=150px>10:30 - 11:00</td> 495 <td width=400px></td> 496 </tr> 497 <tr> 498 <td width=130px>Paper presentations</td> 499 <td width=150px>11:00 - 12:30</td> 500 <td width=400px>Accepted paper presentations (1-4) (each 15 min Talk + 5 min Q&A)</td> 501 </tr> 502 <tr> 503 <td width=130px>Lunch</td> 504 <td width=150px> 12:30 - 13:30</td> 505 <td></td> 506 </tr> 507 <tr> 508 <td width=130px>Keynote II</td> 509 <td width=150px>13:30 - 14:20</td> 510 <td width=400px>Keynote II Assoc. Prof. Zhaochun Ren (45 min Talk + 5 min Q&A)</td> 511 </tr> 512 <tr> 513 <td width=130px>Invited talks</td> 514 <td width=150px>14:20 - 15:10</td> 515 <td width=400px>Invited talks by (2) Paul Lerner and (3) Zeyuan Meng (each 20 min Talk + 5 min Q&A)</td> 516 </tr> 517 <tr> 518 <td width=130px>Coffee break</td> 519 <td width=150px>15:10 - 15:30</td> 520 <td width=400px></td> 521 </tr> 522 <tr> 523 <td width=130px>Invited talks</td> 524 <td width=150px>15:30 - 16:20</td> 525 <td width=400px>Invited talks by (4) Sara Abdollahi and (5) Erlend Frayling (each 20 min Talk + 5 min Q&A) 526 </td> 527 </tr> 528 <tr> 529 <td width=130px>Closing remarks</td> 530 <td width=150px>16:20 - 16:30</td> 531 <td width=400px></td> 532 </tr> 533 </table> 534 </div> 535</section> 536 <section id="organizer" class="bg-mid-gray"> 537 <div class="container"> 538 <div class="row"> 539 <div class="col-lg-12 text-center" style="padding-bottom: 20px;"> 540 <h2 class="section-heading">Workshop Organizers</h2> 541 </div> 542 </div> 543 544 <div class="row"> 545 546 547 548 <div class="col-sm-3"> 549 <div class="team-member text-center"> <!-- Added text-center here for center alignment -->
550 <img src="assets/img/zaiqiaomeng.jpg" class="img-responsive img-circle" alt="Dr. Zaiqiao Meng" 551 width="600" height="600"> 552 <h4><a href="https://mengzaiqiao.github.io/">Dr. Zaiqiao Meng</a></h4> 553 <p class="text-muted">Lecturer</p> 554 <p class="text-muted">University of Glasgow</p> 555 </div> 556 </div> 557 558 559 560 <div class="col-sm-3"> 561 <div class="team-member text-center"> <!-- Added text-center here for center alignment --> 562 <img src="assets/img/shangsongliang.jpg" class="img-responsive img-circle" alt="Dr. Shangsong Liang" 563 width="600" height="600"> 564 <h4><a href="https://mbzuai.ac.ae/study/faculty/shangsong-liang/">Dr. Shangsong Liang</a></h4> 565 <p class="text-muted">Assistant Professor</p> 566 <p class="text-muted">MBZUAI</p> 567 </div> 568 </div> 569 570 571 572 <div class="col-sm-3"> 573 <div class="team-member text-center"> <!-- Added text-center here for center alignment --> 574 <img src="assets/img/xinxin.jpg" class="img-responsive img-circle" alt="Dr. Xin Xin" 575 width="600" height="600"> 576 <h4><a href="https://xinxin-me.github.io/">Dr. Xin Xin</a></h4> 577 <p class="text-muted">Assistant Professor</p> 578 <p class="text-muted">Shandong University</p> 579 </div> 580 </div> 581 582 583 584 <div class="col-sm-3"> 585 <div class="team-member text-center"> <!-- Added text-center here for center alignment --> 586 <img src="assets/img/gianlucamoro.jpg" class="img-responsive img-circle" alt="Dr. Gianluca Moro" 587 width="600" height="600"> 588 <h4><a href="https://www.unibo.it/sitoweb/gianluca.moro/en">Dr. Gianluca Moro</a></h4> 589 <p class="text-muted">Associate Professor</p> 590 <p class="text-muted">University of Bologna</p> 591 </div> 592 </div> 593 594 595 596 <div class="col-sm-3"> 597 <div class="team-member text-center"> <!-- Added text-center here for center alignment --> 598 <img src="assets/img/evangeloskanoulas.jpeg" class="img-responsive img-circle" alt="Prof. Evangelos Kanoulas" 599 width="600" height="600"> 600 <h4><a href="https://staff.fnwi.uva.nl/e.kanoulas/">Prof. Evangelos Kanoulas</a></h4> 601 <p class="text-muted">Professor</p> 602 <p class="text-muted">University of Amsterdam</p> 603 </div> 604 </div> 605 606 607 608 <div class="col-sm-3"> 609 <div class="team-member text-center"> <!-- Added text-center here for center alignment --> 610 <img src="assets/img/emineyilmaz.jpeg" class="img-responsive img-circle" alt="Prof. Emine Yilmaz" 611 width="600" height="600"> 612 <h4><a href="https://sites.google.com/site/emineyilmaz/home">Prof. Emine Yilmaz</a></h4> 613 <p class="text-muted">Professor</p> 614 <p class="text-muted">University College London</p> 615 </div> 616 </div> 617 618 619 620 621 622 623 </div> 624 625 <!-- Publicity Chairs Section --> 626 <div class="row"> 627 <div class="col-lg-12 text-center" style="padding-top: 40px; padding-bottom: 20px;"> 628 <h2 class="section-subheading">Publicity Chairs</h2> 629 </div> 630 </div> 631 632 <div class="row"> 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 <div class="col-sm-3"> 648 <div class="team-member text-center"> <!-- Added text-center here for center alignment --> 649 <img src="assets/img/giacomo.jpeg" class="img-responsive img-circle" alt="Giacomo Frisoni" 650 width="600" height="600"> 651 <h4><a href="https://scholar.google.com/citations?user=BEZlFiAAAAAJ&hl=en">Giacomo Frisoni</a></h4> 652 <p class="text-muted">
652PhD. Student</p> 653 <p class="text-muted">University of Bologna</p> 654 </div> 655 </div> 656 657 658 659 <div class="col-sm-3"> 660 <div class="team-member text-center"> <!-- Added text-center here for center alignment --> 661 <img src="assets/img/jinyuan.jpg" class="img-responsive img-circle" alt="Jinyuan Fang" 662 width="600" height="600"> 663 <h4><a href="https://scholar.google.com/citations?user=LOWJnPsAAAAJ&hl=en">Jinyuan Fang</a></h4> 664 <p class="text-muted">PhD. Student</p> 665 <p class="text-muted">University of Glasgow</p> 666 </div> 667 </div> 668 669 670 </div> 671 672 </div> 673</section> 674 <section id="contact"> 675 <div class="container"> 676 <div class="row"> 677 <div class="col-lg-12 text-center"> 678 <h2 class="section-heading">Contact</h2> 679 <!--h3 class="section-subheading text-muted">Lorem ipsum dolor sit amet consectetur.</h3--> 680 </div> 681 </div> 682 <div class="row text-justify text-center"> 683 <div class="col-md-12 text-center"> 684 <p class="large text-muted"> 685 <a href="mailto:[email protected]">[email protected]</a> 686 </p> 687 <div class="large text-muted"> 688 Copyright © KEIR@ECIR2024 689 </div> 690 </div> 691 </div> 692 </div> 693</section> 694 695 <!-- jQuery --> 696
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699<script src="assets/js/bootstrap.min.js"></script>
699 700 701 <!-- Plugin JavaScript --> 702
702<script src="http://cdnjs.cloudflare.com/ajax/libs/jquery-easing/1.3/jquery.easing.min.js"></script>
702 703
703<script src="assets/js/classie.js"></script>
703 704
704<script src="assets/js/cbpAnimatedHeader.js"></script>
704 705 706 <!-- Contact Form JavaScript --> 707
707<script src="assets/js/contact_me.js"></script>
707 708 709 <!-- Custom Theme JavaScript --> 710
710<script src="assets/js/agency.js"></script>
710 711 712</body> 713 714</html>
Line numbers count LF bytes from the start of the resource, as the search results do. Vendor segments are library code the classifier recognised; they are stored but not indexed. Bytes are shown as Latin1 characters, one per byte.