# US 8,752,184 B1 · Spam detection for user-generated multimedia items based on keyword stuffing > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 8,752,184 B1 - Document ID: US8752184B1 - Status: Granted - Kind: B1 - Application number: 12/015,986 - Filed: 2008-01-17 - Granted: 2014-06-10 - Earliest claimed: 2008-01-17 - Assignees: Google Inc. - Applicants: Varun Kacholia; Ashutosh Garg; David Stoutamire - Inventors: Varun Kacholia; Ashutosh Garg; David Stoutamire - Web page: https://patentgrep.com/patent/US8752184B1 ## CPC - G06F 16/78: Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually - G06F 16/951: Indexing; Web crawling techniques - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) ## Abstract A system, a method, and various software tools enable a video hosting website to automatically identify posted video items that contain spam in the metadata associated with a respective video item. A spam detection tool for user-generated video items based on keyword stuffing is provided that facilitates the detection of spam in the metadata associated with a video item. ## Claims ### Claim 1 A computer-implemented method for spam detection in a collection of multimedia items, comprising: storing the collection of multimedia items in a memory of a computer system, each multimedia item including a description of the item, the description including a plurality of tokens; and for at least one multimedia item: selecting a plurality of portions of the description of the item and for each selected portion counting a total number of unique tokens in the selected portion, wherein unique tokens appearing more than once in the selected portion are counted only once; determining a distribution of unique tokens for the multimedia item using the total number of unique tokens in each selected portion of the multimedia item; and responsive to the distribution of unique tokens exceeding a distribution threshold, marking the multimedia item for a future spam filtering action. ### Claim 2 (depends on 1) The computer implemented method of claim 1, further comprising: indexing the multimedia items remaining in the collection in the index. ### Claim 3 (depends on 1) The computer-implemented method of claim 1, wherein the future spam filtering action is removing the multimedia item from the collection in memory. ### Claim 4 (depends on 1) The computer-implemented method of claim 1, wherein the future spam filtering action is demoting a rank of the multimedia item. ### Claim 5 (depends on 1) The computer-implemented method of claim 1, wherein the distribution is determined using a total number of unique tokens in all portions of the plurality of portions. ### Claim 6 (depends on 1) The computer-implemented method of claim 1, wherein the distribution is determined using an average number of unique tokens in all portions of the plurality of portions. ### Claim 7 (depends on 1) The computer-implemented method of claim 1, wherein the distribution is determined using a minimum number of unique tokens in any portion of the plurality of portions. ### Claim 8 (depends on 1) The computer-implemented method of claim 1, wherein the distribution is determined using a percentage of unique tokens in all portions of the plurality of portions. ### Claim 9 (depends on 1) The computer-implemented method of claim 1, wherein the distribution is determined using a maximum of percentage of unique tokens in any portion of the plurality of portions. ### Claim 10 (depends on 1) The computer-implemented method of claim 1, wherein the distribution is determined using a ratio of number of unique tokens in any portion of the plurality of portions to expected number of unique tokens in the portion. ### Claim 11 (depends on 1) The computer-implemented method of claim 1, wherein the distribution is determined using a ratio of number of instances of a most frequently occurring token to total number of tokens in any portion of the plurality of portions. ### Claim 12 A non-transitory computer readable storage medium containing program code for spam detection in a collection of multimedia items, the program code comprising code for: storing the collection of multimedia items, each multimedia item including a description of the item, the description including a plurality of tokens; and for at least one multimedia item: selecting a plurality of portions of the description of the item and for each selected portion counting a total number of unique tokens in the selected portion, wherein unique tokens appearing more than once in the selected portion are counted only once; determining a distribution of unique tokens for the multimedia item using the total number of unique tokens in each selected portion of the multimedia item; and responsive to the distribution of unique tokens exceeding a distribution threshold, marking the multimedia item for a future spam filtering action. ### Claim 13 (depends on 1) The computer-implemented method of claim 1, wherein the multimedia items are videos. ### Claim 14 (depends on 12) The computer readable storage medium of claim 12, wherein the multimedia items are videos.