2b:null 2c:["$","title",null,{"children":"Research Paper Explorer: Discover Relevant Papers with Recommended System | Kasi Viswanath | Observable"}] 31:Tca9,chart = { const simulation = d3 .forceSimulation(nodes) .force( "link", d3.forceLink(links).id((d) => d.id) ) .force("collide", d3.forceCollide(Math.sqrt(2000) / 2).iterations(4)) .force("boundary", forceBoundary(20, 20, width - 20, height - 20)) .force("charge", d3.forceManyBody()) .force("radial", d3.forceRadial(400)) .force("center", d3.forceCenter(width / 2, height / 2)); const svg = d3.create("svg").attr("viewBox", [0, 0, width, height]); const link = svg .append("g") .attr("stroke", "#999") .attr("stroke-opacity", 0.6) .selectAll("line") .data(links) .join("line") .attr("stroke-width", 1); const nodePapers = svg .append("g") .attr("stroke", "#f47d55") .attr("stroke-width", 1.5) .selectAll("circle") .data(nodes.filter((d) => d.type === "paper")) .join("circle") .attr("r", (d) => citationScale(d.citations)) // .attr("fill", color) .call(drag(simulation)) .on("mouseenter", (evt, d) => { link .attr("display", "none") .filter((l) => l.source.id === d.id || l.target.id === d.id) .attr("display", "block"); }) .on("mouseleave", (evt) => { link.attr("display", "block"); }) .on("click", async (evt, d) => { console.log(evt, d); let res = await recommendPapers(d.paperId); res.recommendedPapers.map((d) => data.push(d)); viewof data.dispatchEvent(new Event("input", { bubbles: true })); mutable level = level + 1; }); nodePapers.append("title").text((d) => d.id); const paperAnimation = nodePapers.transition().duration(50); //Authors const nodeAuthors = svg .append("g") .attr("stroke", "#f9d04e") .attr("stroke-width", 1.5) .selectAll("rect") .data(nodes.filter((d) => d.type != "paper")) .join("rect") .attr("width", 10) .attr("height", 10) // .attr("fill", color) .call(drag(simulation)) .on("mouseenter", (evt, d) => { link .attr("display", "none") .filter((l) => l.source.id === d.id || l.target.id === d.id) .attr("display", "block"); }) .on("mouseleave", (evt) => { link.attr("display", "block"); }) .on("click", async (evt, d) => { console.log(evt, d); let res = await getPapers(d.id); res.map((d) => data.push(d)); viewof data.dispatchEvent(new Event("input", { bubbles: true })); mutable level = level + 1; }); nodeAuthors.append("title").text((d) => authorId[d.id]); // const authorLabels = svg // .selectAll("text") // .data(nodes.filter((d) => d.type != "paper")) // .join("text") // .style("font", "8pt sans-serif") // .style("cursor", "default") // .text((d) => authorId[d.id]); simulation.on("tick", () => { link .attr("x1", (d) => d.source.x) .attr("y1", (d) => d.source.y) .attr("x2", (d) => d.target.x) .attr("y2", (d) => d.target.y); nodePapers.attr("cx", (d) => d.x).attr("cy", (d) => d.y); nodeAuthors.attr("x", (d) => d.x).attr("y", (d) => d.y); // authorLabels.attr("x", (d) => d.x).attr("y", (d) => d.y); }); invalidation.then(() => simulation.stop()); return svg.node(); }32:Tfde,## Introduction Research papers and articles are crucial resources for staying up-to-date with the latest developments in any field of study. These documents are written by experts in their respective areas and provide valuable insights and knowledge to readers. By reading research papers and articles, you can gain a deeper understanding of the theories, methods, and findings that shape your field of interest, and use this knowledge to inform your own work or decision-making However, finding relevant research papers and articles can be a daunting task, especially with the vast amount of literature available today. Traditional search engines often rely on keyword matching, which may not capture the full context or relevance of a particular paper. Fortunately, with the advancement of technology, recommender systems have emerged as a useful tool for identifying relevant papers. These systems use machine learning algorithms to analyze a user's interests and search history, and recommend papers that are most relevant to their needs. By leveraging the power of big data, recommender systems can identify patterns and relationships between papers, making it easier for users to discover and access the most relevant and important research in their field ## Target Audience - Individuals who are interested in or involved in academic research and study. This may include students, researchers, professors, scholars, and professionals in various fields such as science, engineering, social sciences, humanities, and more. - Individuals who are interested in learning about the latest developments and trends in a particular field or those who want to stay updated on the latest research in their industry or profession. ## Data Abstraction(What): - Dataset type: Table, Network - Dataset Availability: Dynamic - Attributes: - Title - Categorical - This attribute describes the title of the paper - Author - Categorical - This attribute describes the authors who published the paper - CitationCount - Quantitative - This attribute describes the published paper citations - Derived Attribute: - Type - based on whether the node is title and author ## Task Abstraction(Why): - **T1** : Locate the paper and Explore the recommended papers [**Locate**,**Features**] - **T2** : Explore the author published papers based on author selection [**Explore**,**Features**] ## Idiom Abstraction - Marks: Point, Line - Channel: - Shape: To identify whether the type is author or paper - Attribute: Type(derived) - Task: T1, T2 - Using seperate - Expressiveness principle - The paper publication details can be represented - Effectiveness principle - The different shape of the nodes indicates different types - Size: To represent the citations count of the paper - Attribute: citationCount - Task: T1, T2 - Using Express - Expressiveness principle - The citation count can be represent in size - Effectiveness principle - Since the size is reasonable different, the bigger the circle the higher the citations ## Insight - The researchers behind the website search usability study cited "The future of crowd work" as a source of inspiration or insight into the potential role of crowd workers in improving website search functionality. Alternatively, they may have referenced the paper to highlight the potential impact of crowd work on the future of work and how it could affect website design and development practices. ## Hypothesis (Madeup Insight) - By exploring the recommended papers and author-published papers based on the user-selected paper, we can enhance the user's knowledge and understanding of the research topic, identify related studies and research gaps, and potentially discover new insights and research directions. [selected] - Understanding the co-authorship patterns of research papers can provide insights into the collaboration dynamics among researchers, the distribution of expertise and knowledge within a research community33:[{"id":"fe06d189442eb95ccd5e78e7b233011b8c825a52d261e7202e199f12ccb3f5acf437790f7e5f07cc64250fe55e8cc2f11312ac173c612f9569154d19072dc84c","href":"https://static.observableusercontent.com/files/fe06d189442eb95ccd5e78e7b233011b8c825a52d261e7202e199f12ccb3f5acf437790f7e5f07cc64250fe55e8cc2f11312ac173c612f9569154d19072dc84c","name":"RecomenderPapers.json","type":"application/json","lastModified":1679393428800.745,"size":49010}] 2f:{"id":"fc53be8f0dc01239","slug":null,"title":"Research Paper Explorer: Discover Relevant Papers with Recommended System","thumbnail":"ee3c567029b19ec136bfd624b1379a73dc785b2e6976a125a23eb26fa3bfabba","access_level":"public","create_time":"$D2023-03-21T06:29:25.855Z","update_time":"$D2023-03-23T03:30:44.434Z","view_time":null,"first_public_time":"$D2023-03-21T06:29:25.855Z","has_unpublished_edits":null,"fork":false,"stars":0,"starred":false,"owner":{"type":"team","id":"b760ea566a896d7d","login":"kasivisu4","name":"Kasi Viswanath","avatar_url":"https://avatars-next.observableusercontent.com/48e36723913e7e5b18b906e1d7cde12fad4146715e78bbf74d3db7969a248b56","tier":"starter_2024"},"version":563,"publish_version":null,"role":null,"authored":false,"authors":[{"type":"individual","id":"fcd94e1c1ca12ae9","login":"kasivisu4","name":"Kasi Viswanath","avatar_url":"https://avatars-next.observableusercontent.com/48e36723913e7e5b18b906e1d7cde12fad4146715e78bbf74d3db7969a248b56","tier":null}],"members":[{"type":"individual","id":"fcd94e1c1ca12ae9","login":"kasivisu4","name":"Kasi Viswanath","avatar_url":"https://avatars-next.observableusercontent.com/48e36723913e7e5b18b906e1d7cde12fad4146715e78bbf74d3db7969a248b56","tier":null,"role":"editor"}],"comments":[{"id":"1d24fd9c4e183567","reply_to_id":null,"content":"Refreshing does not work, it still says the node is not found. What could be the issue?","create_time":"$D2023-04-07T07:10:18.799Z","update_time":null,"resolved":false,"user":{"type":"individual","id":"c1b55e41c39ab2cc","login":"aparnak799","name":"Aparna Krishnan","avatar_url":"https://avatars-next.observableusercontent.com/6753a0acf921239551456a133160847934758fe4e7661d6525748489ce829068","tier":null}},{"id":"90b385725e0c98bc","reply_to_id":null,"content":"I feel like this title could be more insight-based.","create_time":"$D2023-04-07T07:11:15.744Z","update_time":null,"resolved":false,"user":{"type":"individual","id":"c1b55e41c39ab2cc","login":"aparnak799","name":"Aparna Krishnan","avatar_url":"https://avatars-next.observableusercontent.com/6753a0acf921239551456a133160847934758fe4e7661d6525748489ce829068","tier":null}},{"id":"32cdb2106fd06cf5","reply_to_id":null,"content":"Great insight!","create_time":"$D2023-04-07T07:11:34.532Z","update_time":null,"resolved":false,"user":{"type":"individual","id":"c1b55e41c39ab2cc","login":"aparnak799","name":"Aparna Krishnan","avatar_url":"https://avatars-next.observableusercontent.com/6753a0acf921239551456a133160847934758fe4e7661d6525748489ce829068","tier":null}}],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":0,"collection":{"id":"14a0961462b84603","slug":"dataviz","title":"DataViz","owner":{"id":"b760ea566a896d7d","login":"kasivisu4","name":"Kasi Viswanath"}},"type":"notebook","body":{"title":"Research Paper Explorer: Discover Relevant Papers with Recommended System","cells":[{"id":0,"value":"# Research Paper Explorer: Discover Relevant Papers with Recommended System\n\nInsight: To gain insight into the future of crowd work, exploring the concept of Human Responsible Artificial Intelligence within Computer-Human Interaction is essential.\n\nHomework 6: Extracting insights from networks or maps \n- Created by [Kasi Viswanath Vandanapu](https://vandanapuk.sites.northeastern.edu/)\n- Class [CS 7295: Special Topics Course / Information Visualization](https://johnguerra.co/classes/data_visualization_spring_2023/)\n- Professor Name : [John Alexis Guerra Gómez](https://johnguerra.co)\n- [Tweet](https://twitter.com/kasi_vandanapu/status/1638624709620432896) | [Dataset Source](https://www.tesladeaths.com/)\n- [API Source](https://api.semanticscholar.org/api-docs/graph)","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":10,"value":"viewof searchPaper = Inputs.text({\n submit: true,\n label: \"Keyword Search\",\n value: \"The future of crowd work\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":51,"value":"viewof selectedPaper = Inputs.select(\n responsePapers[\"data\"].map((d) => d.title),\n {\n label: \"Paper for recommendations\",\n width: 300\n }\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":544,"value":"## Network for Paper Recommendations","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":477,"value":"Note : Circle are Papers & Square are Authors.
\nPlease refresh the browser in case there is error as data is dynamic \n\n- Selecting Author gives the author published papers\n- Selecting Paper gives the recommendation papers \n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":169,"value":"$31","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":513,"value":"## Demo:\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":447,"value":"$32","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":547,"value":"## Preprocessing","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":184,"value":"async function getPapers(author) {\n const url = `https://api.semanticscholar.org/graph/v1/author/${author}/papers?fields=title,authors,citationCount`;\n let res = await fetch(url, {\n method: \"GET\",\n mode: \"cors\",\n cache: \"no-cache\",\n credentials: \"same-origin\",\n headers: {\n \"Content-Type\": \"application/json\",\n \"x-api-key\": \"QV6KHuzBWR2YAiK4zrj9l2wwFzovRVb29SUY3Y1a\"\n },\n redirect: \"follow\",\n referrerPolicy: \"no-referrer\"\n }).then((res) => res.json());\n return res.data;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":174,"value":"drag = (simulation) => {\n function dragstarted(event) {\n if (!event.active) simulation.alphaTarget(0.3).restart();\n event.subject.fx = event.subject.x;\n event.subject.fy = event.subject.y;\n }\n\n function dragged(event) {\n event.subject.fx = event.x;\n event.subject.fy = event.y;\n }\n\n function dragended(event) {\n if (!event.active) simulation.alphaTarget(0);\n event.subject.fx = null;\n event.subject.fy = null;\n }\n\n return d3\n .drag()\n .on(\"start\", dragstarted)\n .on(\"drag\", dragged)\n .on(\"end\", dragended);\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":277,"value":"citationScale = {\n data;\n return d3\n .scaleLinear()\n .domain([0, d3.max(data.map((d) => d.citationCount))])\n .range([5, 10]);\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":171,"value":"height = 500","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":37,"value":"responsePapers = {\n const url = `https://api.semanticscholar.org/graph/v1/paper/search?query=${searchPaper}&limit=30&fields=title,authors,citationCount`;\n return fetch(url, {\n method: \"GET\",\n mode: \"cors\",\n cache: \"no-cache\",\n credentials: \"same-origin\",\n headers: {\n \"Content-Type\": \"application/json\",\n \"x-api-key\": \"QV6KHuzBWR2YAiK4zrj9l2wwFzovRVb29SUY3Y1a\"\n },\n redirect: \"follow\",\n referrerPolicy: \"no-referrer\"\n }).then((res) => res.json());\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":405,"value":"async function recommendPapers(paper_id) {\n const url = `https://api.semanticscholar.org/recommendations/v1/papers/forpaper/${paper_id}?limit=30&fields=title,authors,citationCount`;\n let res = await fetch(url, {\n method: \"GET\",\n mode: \"cors\",\n cache: \"no-cache\",\n credentials: \"same-origin\",\n headers: {\n \"Content-Type\": \"application/json\",\n \"x-api-key\": \"QV6KHuzBWR2YAiK4zrj9l2wwFzovRVb29SUY3Y1a\"\n },\n redirect: \"follow\",\n referrerPolicy: \"no-referrer\"\n }).then((res) => res.json());\n return res;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":74,"value":"recomenderpapers = {\n const url =\n \"https://api.semanticscholar.org/recommendations/v1/papers/?fields=title,authors,externalIds,citationCount\";\n return fetch(url, {\n method: \"POST\",\n mode: \"cors\",\n cache: \"no-cache\",\n credentials: \"same-origin\",\n headers: {\n \"Content-Type\": \"application/json\",\n \"x-api-key\": \"QV6KHuzBWR2YAiK4zrj9l2wwFzovRVb29SUY3Y1a\"\n },\n redirect: \"follow\",\n referrerPolicy: \"no-referrer\",\n body: JSON.stringify({ positivePaperIds })\n }).then((res) => res.json());\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":119,"value":"nodes = {\n let nodesPresent = new Set();\n data;\n return data\n .map((d) => ({\n id: d.title,\n type: \"paper\",\n citations: d.citationCount,\n paperId: d.paperId\n }))\n .map((d) => {\n if (!nodesPresent.has(d.id)) {\n nodesPresent.add(d.id);\n return d;\n }\n return \"\";\n })\n .filter((d) => d != \"\")\n\n .concat(\n data\n .map((d) => d.authors.map((a) => a.authorId))\n .flat()\n .map((d) => {\n if (!nodesPresent.has(d)) {\n nodesPresent.add(d);\n return d;\n }\n return \"\";\n })\n .filter((d) => d != \"\")\n .map((d) => {\n return { id: d, type: \"author\" };\n })\n );\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":121,"value":"linksPaper = {\n data;\n return data.map((d) => ({ source: selectedPaper, target: d.title }));\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":157,"value":"linksAuthors = {\n data;\n return data\n .map((d) => d.authors.map((a) => ({ source: d.title, target: a.authorId })))\n .flat();\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":164,"value":"links = {\n return linksPaper.concat(linksAuthors).filter((d) => d.target);\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":210,"value":"authorId = {\n let authors = {};\n data.forEach((d) =>\n d.authors.forEach((x) => {\n authors[x.authorId] = x.name;\n })\n );\n return authors;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":116,"value":"viewof data = {\n let target = htl.html` `;\n target.value = recomenderpapers.recommendedPapers\n .concat(responsePapers.data.filter((d) => d.title === selectedPaper)[0])\n .sort((a, b) => a.citationCount < b.citationCount)\n .slice(0, 15);\n return target;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":77,"value":"// API_KEY = \"QV6KHuzBWR2YAiK4zrj9l2wwFzovRVb29SUY3Y1a\"","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":63,"value":"positivePaperIds = [\n responsePapers.data.filter((d) => d.title === selectedPaper)[0][\"paperId\"]\n]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":252,"value":"forceBoundary = require(\"d3-force-boundary\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":424,"value":"mutable level = 0","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W33","stdlib":"1","titling":"auto"}} 30:"$2f:body"