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COMP9312 Data Analytics for Graphs
创建日期：2024-05-30 16:32:22
标签： COMP9312
Data Analytics for Graphs

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COMP9312  Data Analytics for Graphs

Assignment 1
Graph Storage and Graph Traversal
Summary
Submission Submit an electronic copy of all answers on Moodle (only the last submission will be used).
Required Files A .pdf file is required. The file name should be ass1_Zid.pdf
Deadline 9pm Friday 23 June (Sydney Time)
Marks 30 marks (15% toward your total mark for this course)
Late penalty. 5% of max mark will be deducted for each additional day (24hr) after the specified submission time and date. No submission is accepted 5 days (120hr) after
the deadline.
START OF QUESTIONS
Figure 1 Figure 2
Q1. Required knowledge covered by Topic 1.1 (4 marks)
Please determine whether the following statements for the graph in Figure 1 are TRUE or FALSE. (4 marks)
a. In some correct BFS traversal starting from C, A can be traversed before F.
b. In any correct DFS traversal starting from E, G must be traversed after F.
c. In any correct BFS traversal starting from B, I must be traversed after C.
d. In some correct DFS traversal starting from I, F can be traversed before A.
Marking for Q1: 1 mark is given for each correct TRUE/FALSE answer.
Q2. Required knowledge covered by Topic 0 (6 marks)
Consider the undirected graph in Figure 1 stored by the adjacency list. For each vertex, the neighbors are arranged alphabetically (e.g., the neighbor list of A is [B,C,E,I]). Describe
the algorithm to compute all connected components by the disjoint-set data structure. Show the tree structure after each union operation.
Marking for Q2: Full marks are given if each intermediate disjoint-set tree structure is correct.
Q3. Required knowledge covered by Topic 1.1 (6 marks)
Consider the directed graph in Figure 2 stored by the adjacency list. Compute the topological order of vertices in the graph. Show intermediate steps.
Marking for Q3: Full marks are given if the described process of each vertex is correct and the order of vertices are correct.
Q4. Required knowledge covered by Topic 1.1 (7 marks)
We consider an undirected unweighted graph with n vertices and m edges organized by the adjacency list. Given two vertex sets X and Y in the graph, the sizes of two sets are
x=|X|, y=|Y|. Design an algorithm to compute the shortest distance bewteen X and Y (i.e., the smallest shortest distance between all possible pair of vertices from X to Y). Justify
the time complexity of your algorithm.
Marking for Q4: Two factors are evaluated in marking: (1) How good is your time complexity; (2) Does your algorithm match your time complexity. Full marks are given if
your time complexity is not larger than our expected one and your algorithm corresponds with your time complexity.
Q5. Required knowledge covered by Topic 0 (7 marks)
A streaming graph is a graph where edges are added continuously over time. The graph constructed by L most recent arriving edges is defined as the sliding window. An example
in Figure 3 shows a streaming graph with four edges arriving sequentially. The sliding windows for t=3 and t=4 are presented. Given L=3, when the edge (B,C) arrives, the edge
(A,B) expires and is deleted from the sliding window.
Given a streaming graph without any duplicate edge, provide a data structure to efficiently maintain the neighbors of each vertex within the sliding window. Specifically, the data
structure should support three operations: 1) scanning all neighbors of the vertex in the sliding window, 2) inserting a new neighbor when a new edge arrives, and 3) deleting the
expired neighbor. Justify the time complexity of each operation.
Figure 3: The edges (A,B), (C,D), (A,C), and (B,C) are sequentially added to the graph.
Marking for Q5: Two factors are evaluated in marking: (1) How good is your time complexity; (2) Does your algorithm match your time complexity. Full marks are given if your
time complexity is not larger than our expected one and your algorithm corresponds with your time complexity.
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关键词一 关键词二 关键词三 关键词四 关键词五 和法规和的发更好的风格和 ECON 615 FINC 612 CSC148 COMP 639 ACCT 203 ACCT 211 PSYC 101 MTH2009 COMP52315 PSYCO 432 statistics MATH4063 11 xxx 1 MA1MSP MAST30028 MATH3888 CS341 EEE30002 ES2F5 MCD4160 CC0933 ECON 1101 MCHM3001 CHEM3118 COMMGMT 2511 COMP41280 STAT 631 24T1 IRE379 SENG365 ECON433 FIT3139 MATH4602 LING5621M FINS5516 ECON3208 MN2177 L2 SM EEET1415 Finance DS4023 COMP3004 7CCSMRTS K1S5B6 Stat230 CSCI4211 CSI2132 ECON30130 MAS6100 ENVS222 COM2107 INFO1112 STAT 4004 FIT2100 comp2022 COMP4691 Physics 307 Econ 659 probability CSCI316 fir29 CSCI203 COMP3160 COMP6714 INFO1113 Physics 7B Physics Photonics S203031 STAT2005 COMP90015 CSCI 2110 CSCC46 Information CSC477 COMP4650 Statistical COMP 346 COMP1017 ELEC340 MATH1007 Programming function STAT 244 CS 134 Java cse13s Math 108A FW20 ECON3389 CSE 130 Science 331 COMP9020 engineering COSC 445 CSE 5523 GAME2012 visualization MATH 235 Math 370 CSC343 COGS 108 EE524 COMP10200 STAT 416 3FK4 MSCI 311 ECON6113 ACC40700 EMESTER1 MAS8383 ECO 512 STAT 8310 CMN3102 MA577 CMPT 225 COMP0045 Methods Equations MATH 113 Math 3283W ICS-33 EN4302/ENT603 BIA B350F MA318 MTHM506 MECH 5315M ECONOMICS MAS8382 COM 2004 PX3142 XJEL 3662 STAT 231 MGT B399F PX4131 COM2108 30AM MSCI521 ECONM1015 ACFI304 GR5241 MATH10101 ECON 2070 COMS31900 EFIM20011 CSE 250B ACSE-5 STAT4207 SOFT2412 ELEC 331 AY2020 MSIN0209 FIT2094 CS 241L ST404 CS 411 3D CA3 INF4002 COMP3506 SIT718 CS 188 CS 170 MATH 138 CSE 251A CMT118 DATA5207 CMPT307 CMPT459 T1 PGEE11108 COSC 3P32 ME 163 MATH96007 7QQMM203 EE6227 BA 574 STA 4234 ECO206Y1Y ECO2008 MT2300 MATH 11158 CS 527 MACM 316 CSE474 2DI70 ISE 525 COMP3411 EMAT30007 7CCSMBDT MFIN704 MFIN704W21 MfIB ECE 438 CS 436 F36 CS5344 FE 621A FE621 TBA 612 ECM3151 ECMM422 MF1 MSIN0107 ESSMENT CS 5854 MFIT 5008 MIPS R4000 ENG5274 BU52018 ENG2079 BIOA02 STA2570 F0 INF553 STAT 440 STAT3008 COMP9417 COMP6451 6COM1042 BU52006 ST303 HW-1 CISC-235 CS 510 MATH3161 ECN 140 ECE391 Comp 3613 CVEN 9625 PRG455 UESTION 1 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